---------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\rum842\Dropbox\3.3 Madmen\2 Data Paper\Stata Files\Replication Files\Madman R
> egressions.log
  log type:  text
 opened on:   4 Jul 2019, 13:39:14

. 
. 
. *************************** DESCRIPTIVE STATISTICS AND BACKGROUND *******************************
> ******
. 
. * Table A1: Regression Used to Predict Number of Articles
. use "Lexis-Nexis Articles with Extra Variables.dta", clear

. eststo: tobit total_art leadertime pop rgdppc dem perm_mem eng_lang us i.region i.year, ll(0)

Refining starting values:

Grid node 0:   log likelihood = -6580.8878

Fitting full model:

Iteration 0:   log likelihood = -6580.8878  
Iteration 1:   log likelihood = -6580.8878  

Tobit regression                                Number of obs     =        654
                                                   Uncensored     =        654
Limits: lower = 0                                  Left-censored  =          0
        upper = +inf                               Right-censored =          0

                                                LR chi2(35)       =     920.37
                                                Prob > chi2       =     0.0000
Log likelihood = -6580.8878                     Pseudo R2         =     0.0654

----------------------------------------------------------------------------------
       total_art |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
      leadertime |   12.98654   2.734647     4.75   0.000     7.616229    18.35685
             pop |   3.432345   2.449701     1.40   0.162    -1.378387    8.243077
          rgdppc |   .0602227   .0326162     1.85   0.065    -.0038291    .1242744
             dem |  -364.9466   631.4533    -0.58   0.564    -1604.997    875.1038
        perm_mem |   6488.081   1020.875     6.36   0.000     4483.282     8492.88
        eng_lang |   10808.43   949.0705    11.39   0.000     8944.645    12672.22
              us |   44588.24    1635.82    27.26   0.000     41375.81    47800.67
                 |
          region |
              2  |   1372.152   919.8532     1.49   0.136    -434.2589    3178.564
              3  |   2116.121   898.8072     2.35   0.019     351.0395    3881.202
              4  |   3932.887   935.7629     4.20   0.000     2095.232    5770.542
              5  |   1769.656   817.0311     2.17   0.031     165.1669    3374.144
                 |
            year |
           1987  |   722.5982   2162.146     0.33   0.738    -3523.432    4968.629
           1988  |   1127.334   2125.342     0.53   0.596     -3046.42    5301.088
           1989  |   -2157.88   2200.609    -0.98   0.327    -6479.444    2163.685
           1990  |   1169.329   2236.919     0.52   0.601     -3223.54    5562.199
           1991  |   2820.156   2107.578     1.34   0.181    -1318.713    6959.025
           1992  |   3993.893   2177.943     1.83   0.067    -283.1601    8270.947
           1993  |   1765.575   2175.296     0.81   0.417     -2506.28     6037.43
           1994  |   3905.965   2124.086     1.84   0.066    -265.3237    8077.253
           1995  |   3562.144   2053.076     1.74   0.083    -469.6948    7593.982
           1996  |   2917.003   2102.248     1.39   0.166      -1211.4    7045.406
           1997  |   3175.432   2087.708     1.52   0.129    -924.4163    7275.281
           1998  |   5495.356   2075.523     2.65   0.008     1419.436    9571.276
           1999  |   4536.737   2041.585     2.22   0.027     527.4651     8546.01
           2000  |   4976.653   2004.245     2.48   0.013     1040.708    8912.598
           2001  |   5336.741   2014.379     2.65   0.008     1380.897    9292.586
           2002  |   6021.156   2057.344     2.93   0.004     1980.935    10061.38
           2003  |   7584.413    2019.23     3.76   0.000     3619.042    11549.78
           2004  |   5858.695   1965.103     2.98   0.003     1999.618    9717.771
           2005  |   5483.163   1989.362     2.76   0.006     1576.446    9389.881
           2006  |   6420.734   1959.675     3.28   0.001     2572.317    10269.15
           2007  |   6656.893   2019.251     3.30   0.001     2691.479    10622.31
           2008  |   7017.246   1963.882     3.57   0.000     3160.568    10873.92
           2009  |    6678.74   1989.883     3.36   0.001     2770.999    10586.48
           2010  |   6513.146   1960.157     3.32   0.001     2663.782    10362.51
                 |
           _cons |  -9561.105   2032.988    -4.70   0.000    -13553.49   -5568.715
-----------------+----------------------------------------------------------------
 var(e.total_art)|   3.22e+07    1780103                      2.89e+07    3.59e+07
----------------------------------------------------------------------------------
(est1 stored)

. esttab using appendix.rtf, replace b(3) se(3) lines star(* .10 ** .05 *** .01) compress label tit
> le("Table A1: Tobit Model Used to Predict Expected Articles Per Leader-Year")
(output written to appendix.rtf)

. eststo clear

. predict pred_art, ystar(0,.)

. 
. * Table 1: Leaders Most Frequently in Each Category 
. use "Leader-Year Crazy Scores.dta", clear

. duplicates drop leadid year, force // There are a few leaders who exit and re-enter office in the
>  same year, but all of the variables are coded on a yearly basis, so their entries are exact dupl
> icates.

Duplicates in terms of leadid year

(22 observations deleted)

. collapse (sum) reallycrazy15 (mean) crazyscore, by(leader ccode)

. gsort -reallycrazy15 -crazyscore

. list leader ccode reallycrazy15 crazyscore if reallycrazy15>0

      +----------------------------------------------+
      |         leader   ccode   really~g   crazys~e |
      |----------------------------------------------|
   1. | Saddam Hussein     645          6   .5160714 |
   2. |         Mugabe     552          6   .3104396 |
   3. |    Ahmadinejad     630          3   .6063985 |
   4. |    Kim Jong-Il     731          3   .2987803 |
   5. |      Milosevic     345          2   .1986494 |
      |----------------------------------------------|
   6. |        Qaddafi     620          2   .1401969 |
   7. |  Bucaram Ortiz     130          1   3.230515 |
   8. |         Mahuad     130          1   .4173192 |
   9. | Franco, Itamar     140          1   .4002519 |
  10. |          Botha     560          1   .3240632 |
      |----------------------------------------------|
  11. |          Mbeki     560          1   .2597166 |
  12. |    Kim Il-Sung     731          1   .2403075 |
  13. |    Saakashvili     372          1   .1364541 |
  14. |       Chretien      20          1   .1240838 |
  15. |         Castro      40          1   .0929645 |
      |----------------------------------------------|
  16. |        Hun Sen     811          1   .0263071 |
      +----------------------------------------------+

. 
. use "Leader-Year Crazy Scores.dta", clear

. duplicates drop leadid year, force

Duplicates in terms of leadid year

(22 observations deleted)

. collapse (sum) modcrazy15 (mean) crazyscore, by(leadid leader ccode) //Need leadid because of two
>  Bushes in this category.

. gsort -modcrazy15 -crazyscore

. list leader ccode modcrazy15 crazyscore if modcrazy15>0

      +-------------------------------------------------------+
      |                  leader   ccode   modcra~g   crazys~e |
      |-------------------------------------------------------|
   1. |                  Howard     900          9   .1159171 |
   2. |                   Blair     200          9   .0767134 |
   3. |                    Bush       2          8   .1396907 |
   4. |                  Mugabe     552          7   .3104396 |
   5. |             Kim Jong-Il     731          6   .2987803 |
      |-------------------------------------------------------|
   6. |                   Mbeki     560          6   .2597166 |
   7. |             Hugo Chavez     101          6   .1757978 |
   8. |                 Qaddafi     620          6   .1401969 |
   9. |            Ariel Sharon     666          5   .2042706 |
  10. |          Saddam Hussein     645          4   .5160714 |
      |-------------------------------------------------------|
  11. |                 Sarkozy     220          4   .1335537 |
  12. |                Chretien      20          4   .1240838 |
  13. |                 Yeltsin     365          4   .0899311 |
  14. |                    Bush       2          4   .0635615 |
  15. |                  Reagan       2          4     .02133 |
      |-------------------------------------------------------|
  16. |             Ahmadinejad     630          3   .6063985 |
  17. |                  Castro      40          3   .0929645 |
  18. |                  Jammeh     420          3   .0555507 |
  19. |                    Rudd     900          3    .053764 |
  20. |                Mulroney      20          3   .0382527 |
      |-------------------------------------------------------|
  21. |                   Hawke     900          3   .0373757 |
  22. |                Museveni     500          3   .0353556 |
  23. |                Afeworki     531          3   .0332771 |
  24. |                  Harper      20          3   .0206986 |
  25. |             Saakashvili     372          2   .1364541 |
      |-------------------------------------------------------|
  26. |                   Lange     920          2   .1001635 |
  27. |                Obasanjo     475          2   .0769522 |
  28. |                   Brown     200          2   .0561868 |
  29. |               Musharraf     770          2   .0469507 |
  30. |                 Keating     900          2    .038602 |
      |-------------------------------------------------------|
  31. |               Netanyahu     666          2   .0341628 |
  32. |              Berlusconi     325          2   .0324104 |
  33. |              Lukashenko     370          2   .0304918 |
  34. |    Mahatir Bin Mohammad     820          2    .023285 |
  35. |                  Chirac     220          2   .0194167 |
      |-------------------------------------------------------|
  36. |              Mitterrand     220          2   .0159231 |
  37. |                Thatcher     200          2   .0141696 |
  38. |               Al-Bashir     625          2    .013793 |
  39. |            Kim Campbell      20          1   .4583543 |
  40. |                   Botha     560          1   .3240632 |
      |-------------------------------------------------------|
  41. |             Kim Il-Sung     731          1   .2403075 |
  42. |            Pratap Singh     750          1   .2131041 |
  43. |               Milosevic     345          1   .1986494 |
  44. |                 Habibie     850          1   .1629981 |
  45. |          Hatoyama Yukio     740          1   .1430748 |
      |-------------------------------------------------------|
  46. |                   Barak     666          1   .1133628 |
  47. |               Hashimoto     740          1   .0983408 |
  48. |                 Mandela     560          1   .0845914 |
  49. |                Aristide      41          1   .0792496 |
  50. |                 Estrada     840          1   .0730399 |
      |-------------------------------------------------------|
  51. |                 Nasheed     781          1   .0424538 |
  52. |                  Gusmao     860          1   .0403192 |
  53. |            Kim Dae Jung     732          1   .0392425 |
  54. |              Yushchenko     369          1   .0354706 |
  55. |                  Olmert     666          1   .0351155 |
      |-------------------------------------------------------|
  56. |                  Taylor     450          1   .0330026 |
  57. |       Junichiro Koizumi     740          1   .0326475 |
  58. |           Lula da Silva     140          1   .0306693 |
  59. |               Ian Khama     571          1   .0281977 |
  60. |          Chen Shui-bian     713          1   .0230466 |
      |-------------------------------------------------------|
  61. |               Gorbachev     365          1   .0225466 |
  62. | Gloria Macapagal-Arroyo     840          1   .0204361 |
  63. |                Vajpayee     750          1   .0183284 |
  64. |                   Ahern     205          1   .0165045 |
  65. |            Hamid Karzai     700          1    .015399 |
      |-------------------------------------------------------|
  66. |                 Niyazov     701          1   .0138415 |
  67. |               Than Shwe     775          1   .0119104 |
  68. |                   Obama       2          1   .0115777 |
  69. |                  Nujoma     565          1   .0110006 |
  70. |                   Putin     365          1    .006823 |
      |-------------------------------------------------------|
  71. |                   Major     200          1   .0067107 |
  72. |                 Clinton       2          1   .0023103 |
      +-------------------------------------------------------+

. 
. * Table A2 and Table A3: Summary Statistics
. use "Dyadic Crazy Leader Data.dta", clear

. tabstat initMID crazyscore_l1a crazyscore_l1b reallycrazy15a modcrazy15a reallycrazy15b modcrazy1
> 5b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig d
> istance dyadlength peaceyrs if pol_rel==1, statistics(mean sd median min max) column(statistics) 
> format(%9.0g)

    variable |      mean        sd       p50       min       max
-------------+--------------------------------------------------
     initMID |  .0069299  .0829574         0         0         1
crazys~e_l1a |  .0233717    .13445         0         0   6.46103
crazys~e_l1b |  .0233717    .13445         0         0   6.46103
reallycr~15a |  .0045272  .0671323         0         0         1
 modcrazy15a |  .1197543  .3246761         0         0         1
reallycr~15b |  .0045272  .0671323         0         0         1
 modcrazy15b |  .1197543  .3246761         0         0         1
recentMID~ra |  .5068011  .7874502        .2         0       4.8
recentMID~rb |  .5068011  .7874502        .2         0       4.8
       cinca |  .0309068  .0488247  .0072936  6.51e-06  .2081897
       cincb |  .0309068  .0488247  .0072936  6.51e-06  .2081897
    cincperc |        .5  .2399453        .5  .0021008  .9978992
        dema |  .5343761  .4988196         1         0         1
        demb |  .5343761  .4988196         1         0         1
    jointdem |  .2881252  .4528922         0         0         1
  landcontig |  .1506208  .3576809         0         0         1
    distance |  3.870967  2.783427     3.851      .005    11.989
  dyadlength |   .728538  .3427454         1  .0027397   1.00274
    peaceyrs |  39.61381  36.88617        33         0       194
----------------------------------------------------------------

. use "Crazy Leader MID Data", clear

. tabstat recip crazyscore_l1a crazyscore_l1b reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b
>  recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig dis
> tance in1hostlev, statistics(mean sd median min max) column(statistics) format(%9.0g)

    variable |      mean        sd       p50       min       max
-------------+--------------------------------------------------
       recip |  .4178303   .493467         0         0         1
crazys~e_l1a |  .0651159  .3517989         0         0  3.457386
crazys~e_l1b |  .1151667  .4330929         0         0  3.457386
reallycr~15a |  .0192539  .1374989         0         0         1
 modcrazy15a |  .1167268  .3212879         0         0         1
reallycr~15b |  .0646651  .2460761         0         0         1
 modcrazy15b |  .0773672  .2673276         0         0         1
recentMID~ra |  .8029554  .8976084        .5         0       4.4
recentMID~rb |  .4972576  .6870348       .25         0       4.8
       cinca |  .0260662  .0452176   .007533  .0000167  .2081897
       cincb |  .0172775   .037676  .0040643  .0000113  .2081897
    cincperc |  .4822821  .1769112  .4986559  .0023474  .9972715
        dema |   .396348  .4894012         0         0         1
        demb |  .3372718  .4730326         0         0         1
    jointdem |   .132116  .3387988         0         0         1
  landcontig |  .5531686  .4974323         1         0         1
    distance |  1.521264  1.883991      .784      .005    11.718
  in1hostlev |  3.259936  .6616171         3         2         4
----------------------------------------------------------------

. 
. * Figure A1
. use "Leader-Year Crazy Scores.dta", clear

. _pctile crazyscore_l1 if crazyscore_l1>0, nq(100)

. return list

scalars:
                 r(r1) =  .0442991182208061
                 r(r2) =  .0467793345451355
                 r(r3) =  .0476357005536556
                 r(r4) =  .0502181686460972
                 r(r5) =  .0603422708809376
                 r(r6) =  .0614456199109554
                 r(r7) =  .0661906078457832
                 r(r8) =  .0677362531423569
                 r(r9) =  .0692779198288918
                r(r10) =  .0693926140666008
                r(r11) =  .071611113846302
                r(r12) =  .0783344581723213
                r(r13) =  .0879413485527039
                r(r14) =  .092306099832058
                r(r15) =  .0932090654969215
                r(r16) =  .0961692631244659
                r(r17) =  .0979361608624458
                r(r18) =  .1039784774184227
                r(r19) =  .1082009598612785
                r(r20) =  .1113260686397552
                r(r99) =  3.457385778427124
                r(r98) =  2.780514478683472
                r(r97) =  1.91818630695343
                r(r96) =  1.567901134490967
                r(r95) =  1.510160088539124
                r(r94) =  1.234074592590332
                r(r93) =  1.069194436073303
                r(r92) =  1.04429030418396
                r(r91) =  .9334554672241211
                r(r90) =  .9306531548500061
                r(r89) =  .8879795074462891
                r(r88) =  .8098568320274353
                r(r87) =  .7947966456413269
                r(r86) =  .7365983128547668
                r(r85) =  .7090877294540405
                r(r84) =  .6684605479240417
                r(r83) =  .6352318525314331
                r(r82) =  .6250128149986267
                r(r81) =  .6205912232398987
                r(r80) =  .5687819719314575
                r(r79) =  .566435694694519
                r(r78) =  .5509978532791138
                r(r77) =  .5097585320472717
                r(r76) =  .456397145986557
                r(r75) =  .4468709528446198
                r(r74) =  .4359657168388367
                r(r73) =  .4102190434932709
                r(r72) =  .4085381329059601
                r(r71) =  .3930822610855103
                r(r70) =  .3900825977325439
                r(r69) =  .3730374872684479
                r(r68) =  .3652150928974152
                r(r67) =  .3502992391586304
                r(r66) =  .3352558016777039
                r(r65) =  .3163582980632782
                r(r64) =  .3006355762481689
                r(r63) =  .2950222790241241
                r(r62) =  .2903992235660553
                r(r61) =  .2861495316028595
                r(r60) =  .2780023515224457
                r(r59) =  .2760235667228699
                r(r58) =  .2699138522148132
                r(r57) =  .2602784931659698
                r(r56) =  .2550368010997772
                r(r55) =  .2486804872751236
                r(r54) =  .2457668036222458
                r(r53) =  .2451559454202652
                r(r52) =  .239437147974968
                r(r51) =  .2363018989562988
                r(r50) =  .2353062331676483
                r(r49) =  .234919548034668
                r(r48) =  .2325224727392197
                r(r47) =  .2310179769992828
                r(r46) =  .2255819886922836
                r(r45) =  .221757560968399
                r(r44) =  .2155858427286148
                r(r43) =  .2142358422279358
                r(r42) =  .2122688740491867
                r(r41) =  .2114418745040894
                r(r40) =  .2049327492713928
                r(r39) =  .2031317204236984
                r(r38) =  .1982326507568359
                r(r37) =  .1958852857351303
                r(r36) =  .1873940527439117
                r(r35) =  .183992475271225
                r(r34) =  .1815536320209503
                r(r33) =  .1760090440511703
                r(r32) =  .1712538152933121
                r(r31) =  .1581753790378571
                r(r30) =  .1545189619064331
                r(r29) =  .1532773971557617
                r(r28) =  .1466269344091415
                r(r27) =  .1430357545614243
                r(r26) =  .1404619067907333
                r(r25) =  .1349087506532669
                r(r24) =  .1254200488328934
                r(r23) =  .1238302439451218
                r(r22) =  .119976781308651
                r(r21) =  .1188426241278648

. _pctile crazyscore_l1 if crazyscore_l1>0, nq(20)

. return list

scalars:
                 r(r1) =  .0603422708809376
                 r(r2) =  .0693926140666008
                 r(r3) =  .0932090654969215
                 r(r4) =  .1113260686397552
                 r(r5) =  .1349087506532669
                 r(r6) =  .1545189619064331
                 r(r7) =  .183992475271225
                 r(r8) =  .2049327492713928
                 r(r9) =  .221757560968399
                r(r10) =  .2353062331676483
                r(r11) =  .2486804872751236
                r(r12) =  .2780023515224457
                r(r13) =  .3163582980632782
                r(r14) =  .3900825977325439
                r(r15) =  .4468709528446198
                r(r16) =  .5687819719314575
                r(r17) =  .7090877294540405
                r(r18) =  .9306531548500061
                r(r19) =  1.510160088539124

. 
. * Table A5 and Table A6: Check Cook's D Values
. use "Dyadic Crazy Leader Data", clear

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. drop if pol_rel==0
(731,442 observations deleted)

. reg initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera recentMIDs
> _byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs peacey
> rs_sq peaceyrs_cub

      Source |       SS           df       MS      Number of obs   =    62,384
-------------+----------------------------------   F(18, 62365)    =    117.35
       Model |   17.119535        18  .951085279   Prob > F        =    0.0000
    Residual |  505.428538    62,365  .008104362   R-squared       =    0.0328
-------------+----------------------------------   Adj R-squared   =    0.0325
       Total |  522.548073    62,383   .00837645   Root MSE        =    .09002

--------------------------------------------------------------------------------------
             initMID |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .0085384   .0053358     1.60   0.110    -.0019197    .0189964
         modcrazy15a |   .0016706   .0012265     1.36   0.173    -.0007333    .0040745
      reallycrazy15b |   .0823964   .0053358    15.44   0.000     .0719383    .0928545
         modcrazy15b |   .0032275   .0012265     2.63   0.009     .0008236    .0056315
recentMIDs_byleadera |    .007631   .0005943    12.84   0.000     .0064661    .0087959
recentMIDs_byleaderb |   .0023572   .0005943     3.97   0.000     .0011923     .003522
               cinca |  -.0031071   .0098473    -0.32   0.752    -.0224079    .0161936
               cincb |   .0159212   .0098473     1.62   0.106    -.0033795     .035222
            cincperc |   .0001678   .0019283     0.09   0.931    -.0036118    .0039474
                dema |   .0009322   .0011615     0.80   0.422    -.0013444    .0032087
                demb |   .0014863   .0011615     1.28   0.201    -.0007902    .0037629
            jointdem |  -.0045961   .0015056    -3.05   0.002    -.0075471   -.0016451
          landcontig |   .0237006   .0012079    19.62   0.000     .0213332     .026068
            distance |  -.0006093   .0001675    -3.64   0.000    -.0009376    -.000281
          dyadlength |   .0076644   .0011852     6.47   0.000     .0053413    .0099875
            peaceyrs |    -.00113   .0000552   -20.48   0.000    -.0012382   -.0010219
         peaceyrs_sq |   .0000138   8.99e-07    15.37   0.000     .0000121    .0000156
        peaceyrs_cub |  -4.75e-08   3.74e-09   -12.70   0.000    -5.49e-08   -4.02e-08
               _cons |   .0134463   .0020489     6.56   0.000     .0094305     .017462
--------------------------------------------------------------------------------------

. predict d, cooksd
(22,520 missing values generated)

. gsort -d

. list leadera leaderb year d if _n<=20 

       +-------------------------------------------------------------+
       |             leadera               leaderb   year          d |
       |-------------------------------------------------------------|
    1. |         Kim Il-Sung              Hosokawa   1994    .023814 |
    2. |      Saddam Hussein                 Kaifu   1991   .0229728 |
    3. |      Saddam Hussein    Khalifah Ath-Thani   1991   .0225774 |
    4. |      Saddam Hussein   Isa Ibn Al-Khalifah   1991   .0221787 |
    5. |      Saddam Hussein                  Kohl   1991   .0217873 |
       |-------------------------------------------------------------|
    6. |      Saddam Hussein        Jabir As-Sabah   1999   .0211545 |
    7. |      Saddam Hussein        Jabir As-Sabah   1991    .020866 |
    8. |      Saddam Hussein        Jabir As-Sabah   1992   .0207632 |
    9. |                Bush             Milosevic   1992   .0204867 |
   10. |                Bush        Saddam Hussein   1991   .0200242 |
       |-------------------------------------------------------------|
   11. |               Blair                Mugabe   2002   .0200168 |
   12. |               Major             Milosevic   1992   .0198779 |
   13. |          Mitterrand             Milosevic   1992   .0198156 |
   14. |                Bush        Saddam Hussein   1992   .0197884 |
   15. |          Mitsotakis             Milosevic   1992   .0194761 |
       |-------------------------------------------------------------|
   16. | Isa Ibn Al-Khalifah        Saddam Hussein   1994   .0192015 |
   17. |             Clinton        Saddam Hussein   1994   .0191825 |
   18. |            Schroder        Saddam Hussein   1999   .0191406 |
   19. |               Major        Saddam Hussein   1991   .0189754 |
   20. |              Chirac        Saddam Hussein   1999   .0189546 |
       +-------------------------------------------------------------+

. 
. use "Crazy Leader MID Data", clear

. drop if tpopa<500 | tpopb<500
(19 observations deleted)

. reg recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera recentMIDs_b
> yleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev

      Source |       SS           df       MS      Number of obs   =       759
-------------+----------------------------------   F(15, 743)      =      2.62
       Model |  9.36470109        15  .624313406   Prob > F        =    0.0007
    Residual |  176.753876       743  .237892161   R-squared       =    0.0503
-------------+----------------------------------   Adj R-squared   =    0.0311
       Total |  186.118577       758   .24553902   Root MSE        =    .48774

--------------------------------------------------------------------------------------
               recip |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1739626   .1341432     1.30   0.195    -.0893822    .4373074
         modcrazy15a |  -.0600306   .0624419    -0.96   0.337    -.1826142     .062553
      reallycrazy15b |  -.1857226   .0781948    -2.38   0.018    -.3392316   -.0322136
         modcrazy15b |  -.0751553   .0701214    -1.07   0.284    -.2128149    .0625042
recentMIDs_byleadera |  -.0141314   .0231515    -0.61   0.542    -.0595816    .0313188
recentMIDs_byleaderb |   .0349519   .0301395     1.16   0.247    -.0242168    .0941206
               cinca |  -.1085381   .5209513    -0.21   0.835     -1.13125    .9141736
               cincb |  -.9496959   .6105386    -1.56   0.120    -2.148282    .2488902
            cincperc |   .0834498   .1417995     0.59   0.556    -.1949256    .3618252
                dema |  -.0749225   .0522093    -1.44   0.152    -.1774179    .0275729
                demb |   -.006721   .0523695    -0.13   0.898    -.1095307    .0960887
            jointdem |  -.0619847   .0875357    -0.71   0.479    -.2338315    .1098621
          landcontig |    .117443   .0466891     2.52   0.012     .0257847    .2091013
            distance |   .0171015   .0133857     1.28   0.202    -.0091767    .0433798
          in1hostlev |  -.0215963   .0293269    -0.74   0.462    -.0791698    .0359771
               _cons |   .4365037   .1316578     3.32   0.001     .1780381    .6949692
--------------------------------------------------------------------------------------

. predict d, cooksd
(153 missing values generated)

. gsort -d

. list leadera leaderb year dispnum3 d if _n<=20 

     +----------------------------------------------------------------------+
     |            leadera              leaderb   year   dispnum3          d |
     |----------------------------------------------------------------------|
  1. |        Kim Jong-Il         Roh Moo Hyun   2007       4479   .0133197 |
  2. |     Saddam Hussein       Jabir As-Sabah   1999       4274   .0130426 |
  3. |        Ahmadinejad            al-Maliki   2007       4536   .0111056 |
  4. |            Noriega               Reagan   1989       3901   .0108982 |
  5. |     Saddam Hussein                Kaifu   1991       3971   .0106331 |
     |----------------------------------------------------------------------|
  6. |        Ahmadinejad            al-Maliki   2010       4547   .0105308 |
  7. |          Netanyahu       Saddam Hussein   1998       4273   .0096568 |
  8. | Ayatollah Khomeini               Reagan   1988       2834   .0092187 |
  9. |              Obama          Hugo Chavez   2010       4506   .0087773 |
 10. |               Bush       Saddam Hussein   1991       3974   .0079136 |
     |----------------------------------------------------------------------|
 11. |               Bush       Saddam Hussein   1992       3552   .0078476 |
 12. |      Deng Xiaoping              Yeltsin   1994       4104   .0069936 |
 13. |             Howard       Saddam Hussein   2003       4273   .0067214 |
 14. |         Rafsanjani                 Bush   1991       3973    .006085 |
 15. |      Deng Xiaoping            Gorbachev   1986       2718   .0059536 |
     |----------------------------------------------------------------------|
 16. |               Bush          Kim Jong-Il   2003       4455   .0059428 |
 17. |        Kim Il-Sung             Hosokawa   1994       4022   .0057383 |
 18. |           Alfonsin     Chiang Ching-Kuo   1986       2579   .0055979 |
 19. |             Reagan   Ayatollah Khomeini   1987       2740    .005465 |
 20. |            Clinton       Saddam Hussein   1997       4273   .0054466 |
     +----------------------------------------------------------------------+

. 
. 
. 
. *************************** DETERMINANTS OF PERCEIVED MADNESS ******************************
. 
. * This is Table A4
. 
. use "Leader-Year Crazy Scores.dta", clear

. duplicates drop leadid year crazyscore modcrazy15_nolag reallycrazy15_nolag dem gwf_personal real
> gdp rebel milservice age gender yrs_in_ofc leveledu recentMIDs_byleader gdp_change_l1, force // T
> here are a few leaders who exit and re-enter office in the same year, but all of the variables ar
> e coded on a yearly basis, so their entries are exact duplicates.

Duplicates in terms of leadid year crazyscore modcrazy15_nolag reallycrazy15_nolag dem gwf_personal
    realgdp rebel milservice age gender yrs_in_ofc leveledu recentMIDs_byleader gdp_change_l1

(22 observations deleted)

. 
. eststo: tobit crazyscore dem gwf_personal realgdp rebel milservice age gender yrs_in_ofc leveledu
>  recentMIDs_byleader gdp_change_l1, ll(0)

Refining starting values:

Grid node 0:   log likelihood = -3025.7223

Fitting full model:

Iteration 0:   log likelihood = -3025.7223  
Iteration 1:   log likelihood = -1439.2805  
Iteration 2:   log likelihood = -569.72661  
Iteration 3:   log likelihood = -475.49869  
Iteration 4:   log likelihood = -369.74955  
Iteration 5:   log likelihood = -338.23825  
Iteration 6:   log likelihood = -334.32487  
Iteration 7:   log likelihood = -334.28447  
Iteration 8:   log likelihood = -334.28444  

Tobit regression                                Number of obs     =      2,512
                                                   Uncensored     =         85
Limits: lower = 0                                  Left-censored  =      2,427
        upper = +inf                               Right-censored =          0

                                                LR chi2(11)       =     118.18
                                                Prob > chi2       =     0.0000
Log likelihood = -334.28444                     Pseudo R2         =     0.1502

-------------------------------------------------------------------------------------
         crazyscore |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
                dem |   .5960599   .1704602     3.50   0.000     .2618023    .9303176
       gwf_personal |   .2361014   .1905394     1.24   0.215    -.1375297    .6097326
            realgdp |   .0069224   .0043615     1.59   0.113    -.0016302     .015475
              rebel |   .1055022   .1645923     0.64   0.522     -.217249    .4282534
         milservice |  -.0978613   .1641657    -0.60   0.551    -.4197761    .2240534
                age |  -.0047229    .006347    -0.74   0.457    -.0171689    .0077231
             gender |   .1344454    .400572     0.34   0.737    -.6510414    .9199322
         yrs_in_ofc |   .0737766   .0153686     4.80   0.000       .04364    .1039132
           leveledu |  -.1060732   .0792444    -1.34   0.181    -.2614645    .0493182
recentMIDs_byleader |    .627617   .1056625     5.94   0.000      .420422    .8348121
      gdp_change_l1 |  -.0270451   .5415318    -0.05   0.960    -1.088942    1.034852
              _cons |  -2.814697   .6310551    -4.46   0.000    -4.052141   -1.577253
--------------------+----------------------------------------------------------------
   var(e.crazyscore)|   1.283392   .2364314                      .8942764    1.841819
-------------------------------------------------------------------------------------
(est1 stored)

. eststo: probit modcrazy15_nolag dem gwf_personal realgdp rebel milservice age gender yrs_in_ofc l
> eveledu recentMIDs_byleader gdp_change_l1, cluster(leadid)

Iteration 0:   log pseudolikelihood = -323.18401  
Iteration 1:   log pseudolikelihood = -278.12459  
Iteration 2:   log pseudolikelihood = -271.92981  
Iteration 3:   log pseudolikelihood = -271.89034  
Iteration 4:   log pseudolikelihood = -271.89034  

Probit regression                               Number of obs     =      2,512
                                                Wald chi2(11)     =      57.89
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -271.89034               Pseudo R2         =     0.1587

                                      (Std. Err. adjusted for 482 clusters in leadid)
-------------------------------------------------------------------------------------
                    |               Robust
   modcrazy15_nolag |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
                dem |   .5818013   .1816394     3.20   0.001     .2257946     .937808
       gwf_personal |   .2278465   .2173324     1.05   0.294    -.1981172    .6538103
            realgdp |   .0131256   .0091833     1.43   0.153    -.0048733    .0311246
              rebel |  -.0590758   .2419146    -0.24   0.807    -.5332198    .4150682
         milservice |  -.0976854   .2101296    -0.46   0.642    -.5095319    .3141611
                age |  -.0028143   .0069985    -0.40   0.688    -.0165311    .0109026
             gender |   .0591371   .3920948     0.15   0.880    -.7093546    .8276288
         yrs_in_ofc |   .0516484   .0166717     3.10   0.002     .0189725    .0843244
           leveledu |  -.0787609   .0957548    -0.82   0.411    -.2664369    .1089151
recentMIDs_byleader |   .4214227   .1294846     3.25   0.001     .1676376    .6752078
      gdp_change_l1 |   -.045565   .6630732    -0.07   0.945    -1.345165    1.254034
              _cons |  -2.463007   .5491356    -4.49   0.000    -3.539293   -1.386721
-------------------------------------------------------------------------------------
(est2 stored)

. eststo: probit reallycrazy15_nolag dem gwf_personal realgdp rebel milservice age yrs_in_ofc level
> edu recentMIDs_byleader gdp_change_l1, cluster(leadid)

Iteration 0:   log pseudolikelihood = -86.617795  
Iteration 1:   log pseudolikelihood =  -72.27703  
Iteration 2:   log pseudolikelihood = -62.121968  
Iteration 3:   log pseudolikelihood = -61.832071  
Iteration 4:   log pseudolikelihood = -61.821496  
Iteration 5:   log pseudolikelihood = -61.821457  
Iteration 6:   log pseudolikelihood = -61.821457  

Probit regression                               Number of obs     =      2,512
                                                Wald chi2(10)     =      42.90
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -61.821457               Pseudo R2         =     0.2863

                                      (Std. Err. adjusted for 482 clusters in leadid)
-------------------------------------------------------------------------------------
                    |               Robust
reallycrazy15_nolag |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
                dem |   .1980807   .3294339     0.60   0.548    -.4475978    .8437592
       gwf_personal |   .0958772    .231093     0.41   0.678    -.3570568    .5488112
            realgdp |  -.0280377   .0258963    -1.08   0.279    -.0787934    .0227181
              rebel |   .4333965   .3020291     1.43   0.151    -.1585698    1.025363
         milservice |  -.0676047    .260023    -0.26   0.795    -.5772404    .4420311
                age |  -.0077237   .0118643    -0.65   0.515    -.0309773      .01553
         yrs_in_ofc |   .0955858   .0231235     4.13   0.000     .0502646    .1409071
           leveledu |  -.1068389   .1584002    -0.67   0.500    -.4172976    .2036198
recentMIDs_byleader |   .7329373   .2143027     3.42   0.001     .3129117    1.152963
      gdp_change_l1 |   .3814529   .4150256     0.92   0.358    -.4319822    1.194888
              _cons |  -3.348307   .8636741    -3.88   0.000    -5.041077   -1.655537
-------------------------------------------------------------------------------------
(est3 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A4: Determinants of Perceived Madness")
(output written to appendix.rtf)

. eststo clear

. 
. 
. ***************************** GENERAL DETERRENCE RESULTS ****************************************
> ****
. 
. use "Dyadic Crazy Leader Data", clear

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. 
. eststo: probit initMID crazyscore_l1a crazyscore_l1b recentMIDs_byleadera recentMIDs_byleaderb ci
> nca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs peaceyrs_sq peaceyr
> s_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2474.9323  
Iteration 2:   log pseudolikelihood = -2299.0434  
Iteration 3:   log pseudolikelihood = -2292.0196  
Iteration 4:   log pseudolikelihood = -2291.9637  
Iteration 5:   log pseudolikelihood = -2291.9637  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(16)     =     861.59
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2291.9637               Pseudo R2         =     0.2462

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_l1a |   .2031248   .0837777     2.42   0.015     .0389235    .3673262
      crazyscore_l1b |    .384957   .0609813     6.31   0.000     .2654358    .5044781
recentMIDs_byleadera |   .2356438   .0307944     7.65   0.000     .1752878    .2959998
recentMIDs_byleaderb |   .0610759   .0314035     1.94   0.052    -.0004739    .1226256
               cinca |   1.891244   .7529235     2.51   0.012     .4155411    3.366947
               cincb |   1.363694    .572092     2.38   0.017     .2424141    2.484974
            cincperc |  -.0133942   .1646554    -0.08   0.935    -.3361129    .3093244
                dema |   .1283482   .0615412     2.09   0.037     .0077297    .2489668
                demb |   .1027609   .0609891     1.68   0.092    -.0167755    .2222973
            jointdem |  -.5016225   .1068106    -4.70   0.000    -.7109674   -.2922776
          landcontig |   .5312343   .0714525     7.43   0.000       .39119    .6712786
            distance |   -.120174    .024864    -4.83   0.000    -.1689066   -.0714414
          dyadlength |   .6712876   .0815593     8.23   0.000     .5114343    .8311409
            peaceyrs |  -.0416752   .0040569   -10.27   0.000    -.0496266   -.0337239
         peaceyrs_sq |   .0005203   .0000764     6.81   0.000     .0003705    .0006701
        peaceyrs_cub |  -1.78e-06   3.65e-07    -4.87   0.000    -2.49e-06   -1.06e-06
               _cons |  -2.675771   .1476899   -18.12   0.000    -2.965238   -2.386304
--------------------------------------------------------------------------------------
(est1 stored)

. 
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood =  -2459.833  
Iteration 2:   log pseudolikelihood = -2293.9348  
Iteration 3:   log pseudolikelihood = -2287.2539  
Iteration 4:   log pseudolikelihood = -2287.2008  
Iteration 5:   log pseudolikelihood = -2287.2008  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     860.71
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2287.2008               Pseudo R2         =     0.2478

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1621716   .2107845     0.77   0.442    -.2509584    .5753017
         modcrazy15a |   .0975225   .0706388     1.38   0.167     -.040927    .2359721
      reallycrazy15b |   .9070658   .1403182     6.46   0.000     .6320472    1.182084
         modcrazy15b |   .1595739   .0746848     2.14   0.033     .0131944    .3059535
recentMIDs_byleadera |   .2315828   .0308084     7.52   0.000     .1711994    .2919661
recentMIDs_byleaderb |   .0483649    .031784     1.52   0.128    -.0139306    .1106603
               cinca |   1.788244   .7723971     2.32   0.021     .2743731    3.302114
               cincb |   1.404199   .5834358     2.41   0.016     .2606862    2.547712
            cincperc |  -.0193573   .1707087    -0.11   0.910    -.3539403    .3152257
                dema |   .1050834   .0607855     1.73   0.084    -.0140541    .2242209
                demb |     .10156   .0616813     1.65   0.100    -.0193332    .2224531
            jointdem |  -.4886537    .106507    -4.59   0.000    -.6974036   -.2799038
          landcontig |   .5386236   .0727528     7.40   0.000     .3960307    .6812165
            distance |  -.1208431   .0244468    -4.94   0.000     -.168758   -.0729282
          dyadlength |   .6325686   .0776553     8.15   0.000     .4803669    .7847703
            peaceyrs |  -.0423802   .0040415   -10.49   0.000    -.0503013    -.034459
         peaceyrs_sq |    .000534   .0000749     7.13   0.000     .0003872    .0006808
        peaceyrs_cub |  -1.83e-06   3.55e-07    -5.17   0.000    -2.53e-06   -1.14e-06
               _cons |  -2.636196   .1491854   -17.67   0.000    -2.928593   -2.343798
--------------------------------------------------------------------------------------
(est2 stored)

. margins, at(modcrazy15b=0 reallycrazy15b=0) saving(file1, replace) 

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycr~15b    =           0
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0078484   .0005041    15.57   0.000     .0068604    .0088364
------------------------------------------------------------------------------
(note: file file1.dta not found)

. margins, at(modcrazy15b=1 reallycrazy15b=0) saving(file2, replace)

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycr~15b    =           0
               modcrazy15b     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0110839   .0017623     6.29   0.000     .0076299     .014538
------------------------------------------------------------------------------
(note: file file2.dta not found)

. margins, at(modcrazy15b=0 reallycrazy15b=1) saving(file3, replace)

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycr~15b    =           1
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |      .0458   .0109364     4.19   0.000      .024365     .067235
------------------------------------------------------------------------------
(note: file file3.dta not found)

. combomarginsplot file1 file2 file3, recast(bar)

  Variables that uniquely identify margins: _filenumber

. graph save Graph "Deterrence_Dum.gph", replace
(note: file Deterrence_Dum.gph not found)
(file Deterrence_Dum.gph saved)

. // Note: The madness variables all have lags built in.
. 
. // It is not clear visually if the difference between the predicted probabilities for no and slig
> ht madness reputation is significant, so I test it.
. probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera recentM
> IDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs pea
> ceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood =  -2459.833  
Iteration 2:   log pseudolikelihood = -2293.9348  
Iteration 3:   log pseudolikelihood = -2287.2539  
Iteration 4:   log pseudolikelihood = -2287.2008  
Iteration 5:   log pseudolikelihood = -2287.2008  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     860.71
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2287.2008               Pseudo R2         =     0.2478

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1621716   .2107845     0.77   0.442    -.2509584    .5753017
         modcrazy15a |   .0975225   .0706388     1.38   0.167     -.040927    .2359721
      reallycrazy15b |   .9070658   .1403182     6.46   0.000     .6320472    1.182084
         modcrazy15b |   .1595739   .0746848     2.14   0.033     .0131944    .3059535
recentMIDs_byleadera |   .2315828   .0308084     7.52   0.000     .1711994    .2919661
recentMIDs_byleaderb |   .0483649    .031784     1.52   0.128    -.0139306    .1106603
               cinca |   1.788244   .7723971     2.32   0.021     .2743731    3.302114
               cincb |   1.404199   .5834358     2.41   0.016     .2606862    2.547712
            cincperc |  -.0193573   .1707087    -0.11   0.910    -.3539403    .3152257
                dema |   .1050834   .0607855     1.73   0.084    -.0140541    .2242209
                demb |     .10156   .0616813     1.65   0.100    -.0193332    .2224531
            jointdem |  -.4886537    .106507    -4.59   0.000    -.6974036   -.2799038
          landcontig |   .5386236   .0727528     7.40   0.000     .3960307    .6812165
            distance |  -.1208431   .0244468    -4.94   0.000     -.168758   -.0729282
          dyadlength |   .6325686   .0776553     8.15   0.000     .4803669    .7847703
            peaceyrs |  -.0423802   .0040415   -10.49   0.000    -.0503013    -.034459
         peaceyrs_sq |    .000534   .0000749     7.13   0.000     .0003872    .0006808
        peaceyrs_cub |  -1.83e-06   3.55e-07    -5.17   0.000    -2.53e-06   -1.14e-06
               _cons |  -2.636196   .1491854   -17.67   0.000    -2.928593   -2.343798
--------------------------------------------------------------------------------------

. margins, at(modcrazy15b=0 reallycrazy15b=0) at(modcrazy15b=1 reallycrazy15b=0) at(modcrazy15b=0 r
> eallycrazy15b=1) coeflegend post

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()

1._at        : reallycr~15b    =           0
               modcrazy15b     =           0

2._at        : reallycr~15b    =           0
               modcrazy15b     =           1

3._at        : reallycr~15b    =           1
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .0078484  _b[1bn._at]
          2  |   .0110839  _b[2._at]
          3  |      .0458  _b[3._at]
------------------------------------------------------------------------------

. test _b[1bn._at]=_b[2._at]

 ( 1)  1bn._at - 2._at = 0

           chi2(  1) =    3.51
         Prob > chi2 =    0.0609

. 
. 
. ***************************** CRISIS BARGAINING RESULTS *****************************************
> *****
. 
. use "Crazy Leader MID Data", clear

. drop if tpopa<500 | tpopb<500
(19 observations deleted)

. 
. eststo: probit recip crazyscore_l1a crazyscore_l1b recentMIDs_byleadera recentMIDs_byleaderb cinc
> a cincb cincperc dema demb jointdem landcontig distance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -501.64971  
Iteration 2:   log pseudolikelihood = -501.60375  
Iteration 3:   log pseudolikelihood = -501.60374  

Probit regression                               Number of obs     =        759
                                                Wald chi2(13)     =     103.04
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -501.60374               Pseudo R2         =     0.0332

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_l1a |   .2719346   .0628074     4.33   0.000     .1488344    .3950348
      crazyscore_l1b |   .0450703   .1230467     0.37   0.714    -.1960968    .2862374
recentMIDs_byleadera |  -.0395864   .1026612    -0.39   0.700    -.2407987     .161626
recentMIDs_byleaderb |   .0587604   .0935213     0.63   0.530     -.124538    .2420589
               cinca |  -.0774358   2.118166    -0.04   0.971    -4.228964    4.074092
               cincb |  -2.364549   1.560182    -1.52   0.130     -5.42245    .6933509
            cincperc |   .3578057    .550338     0.65   0.516     -.720837    1.436448
                dema |  -.2486833   .2016441    -1.23   0.217    -.6438985    .1465319
                demb |  -.0053515   .1624996    -0.03   0.974     -.323845    .3131419
            jointdem |  -.1240833   .3058119    -0.41   0.685    -.7234637     .475297
          landcontig |   .3873371   .1332602     2.91   0.004     .1261519    .6485223
            distance |    .036906    .039913     0.92   0.355     -.041322     .115134
          in1hostlev |  -.0353528   .1497441    -0.24   0.813    -.3288457    .2581402
               _cons |  -.3976275   .6017508    -0.66   0.509    -1.577037    .7817824
--------------------------------------------------------------------------------------
(est3 stored)

. 
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood =  -498.8694  
Iteration 2:   log pseudolikelihood = -498.78813  
Iteration 3:   log pseudolikelihood = -498.78812  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      84.60
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.78812               Pseudo R2         =     0.0386

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4423026   .1535787     2.88   0.004     .1412939    .7433113
         modcrazy15a |   -.159595    .215091    -0.74   0.458    -.5811657    .2619757
      reallycrazy15b |  -.5487059   .1993739    -2.75   0.006    -.9394715   -.1579403
         modcrazy15b |  -.2073286   .1753272    -1.18   0.237    -.5509635    .1363063
recentMIDs_byleadera |  -.0383996   .1052033    -0.37   0.715    -.2445942     .167795
recentMIDs_byleaderb |   .0984017   .0978663     1.01   0.315    -.0934127    .2902161
               cinca |  -.2385955   2.170636    -0.11   0.912    -4.492963    4.015772
               cincb |   -2.67149   1.577587    -1.69   0.090    -5.763504    .4205247
            cincperc |   .2421607   .5203143     0.47   0.642    -.7776366    1.261958
                dema |  -.1968972     .20101    -0.98   0.327    -.5908695    .1970751
                demb |  -.0160729    .155904    -0.10   0.918    -.3216392    .2894933
            jointdem |  -.1767771   .3013367    -0.59   0.557    -.7673861     .413832
          landcontig |   .3124347   .1356034     2.30   0.021      .046657    .5782124
            distance |   .0465961   .0429648     1.08   0.278    -.0376134    .1308056
          in1hostlev |  -.0574566   .1468887    -0.39   0.696    -.3453532      .23044
               _cons |  -.1794699   .6013917    -0.30   0.765    -1.358176    .9992361
--------------------------------------------------------------------------------------
(est4 stored)

. margins, at(modcrazy15a=0 reallycrazy15a=0) saving(file1, replace)

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycr~15a    =           0
               modcrazy15a     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |    .433882   .0301814    14.38   0.000     .3747277    .4930364
------------------------------------------------------------------------------

. margins, at(modcrazy15a=1 reallycrazy15a=0) saving(file2, replace)

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycr~15a    =           0
               modcrazy15a     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .3742894   .0703678     5.32   0.000      .236371    .5122079
------------------------------------------------------------------------------

. margins, at(modcrazy15a=0 reallycrazy15a=1) saving(file3, replace)

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycr~15a    =           1
               modcrazy15a     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .6024154   .0561964    10.72   0.000     .4922725    .7125582
------------------------------------------------------------------------------

. combomarginsplot file1 file2 file3, recast(bar)

  Variables that uniquely identify margins: _filenumber

. graph save Graph "Recip_Dum.gph", replace
(note: file Recip_Dum.gph not found)
(file Recip_Dum.gph saved)

. // Note: The madness variables all have lags built in.
. 
. * Generate Table 1
. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table 1: Main Results")
(output written to appendix.rtf)

. eststo clear

. 
. * Generate Figure 1
. gr combine Deterrence_Dum.gph Recip_Dum.gph

. graph save Graph "Figure 1.gph", replace
(note: file Figure 1.gph not found)
(file Figure 1.gph saved)

. 
. 
. **************************** INTERACTIONS WITH RELATIVE CAPABILITIES ****************************
> ***********
. 
. use "Dyadic Crazy Leader Data", clear

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b##c.cincperc modcrazy15b##c.cincp
> erc recentMIDs_byleadera recentMIDs_byleaderb cinca cincb dema demb jointdem landcontig distance 
> dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

note: cincperc omitted because of collinearity
Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2451.5936  
Iteration 2:   log pseudolikelihood = -2287.2606  
Iteration 3:   log pseudolikelihood = -2280.2706  
Iteration 4:   log pseudolikelihood = -2280.2109  
Iteration 5:   log pseudolikelihood = -2280.2109  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(20)     =     887.25
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2280.2109               Pseudo R2         =     0.2501

                                          (Std. Err. adjusted for 1,554 clusters in dyadid)
-------------------------------------------------------------------------------------------
                          |               Robust
                  initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------------+----------------------------------------------------------------
           reallycrazy15a |    .155736    .211312     0.74   0.461    -.2584279    .5698999
              modcrazy15a |   .0932442   .0722659     1.29   0.197    -.0483944    .2348828
         1.reallycrazy15b |   1.772823   .2695567     6.58   0.000     1.244502    2.301145
                 cincperc |   .0995088     .18929     0.53   0.599    -.2714928    .4705104
                          |
reallycrazy15b#c.cincperc |
                       1  |  -2.326916   .6483043    -3.59   0.000     -3.59757   -1.056263
                          |
            1.modcrazy15b |   .3180115   .2502498     1.27   0.204    -.1724692    .8084921
                 cincperc |          0  (omitted)
                          |
   modcrazy15b#c.cincperc |
                       1  |  -.2789831   .4147891    -0.67   0.501    -1.091955    .5339885
                          |
     recentMIDs_byleadera |   .2337234   .0308545     7.58   0.000     .1732497    .2941972
     recentMIDs_byleaderb |   .0476348    .031631     1.51   0.132    -.0143609    .1096304
                    cinca |   1.773819   .7714727     2.30   0.021       .26176    3.285878
                    cincb |   1.462958   .5876927     2.49   0.013     .3111017    2.614815
                     dema |   .0999497   .0612297     1.63   0.103    -.0200583    .2199577
                     demb |   .0910988   .0613573     1.48   0.138    -.0291592    .2113569
                 jointdem |  -.4767808   .1072966    -4.44   0.000    -.6870782   -.2664834
               landcontig |   .5378979   .0727073     7.40   0.000     .3953941    .6804017
                 distance |  -.1233834   .0245373    -5.03   0.000    -.1714757   -.0752911
               dyadlength |   .6285653   .0777541     8.08   0.000       .47617    .7809605
                 peaceyrs |  -.0420932   .0040115   -10.49   0.000    -.0499557   -.0342308
              peaceyrs_sq |   .0005316   .0000743     7.16   0.000      .000386    .0006772
             peaceyrs_cub |  -1.83e-06   3.51e-07    -5.20   0.000    -2.51e-06   -1.14e-06
                    _cons |  -2.684774   .1544705   -17.38   0.000     -2.98753   -2.382017
-------------------------------------------------------------------------------------------
(est1 stored)

. margins, dydx(reallycrazy15b) at(cincperc=(0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1)) noatlegend

Average marginal effects                        Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
dy/dx w.r.t. : 1.reallycrazy15b

-----------------------------------------------------------------------------------
                  |            Delta-method
                  |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
0.reallycrazy15b  |  (base outcome)
------------------+----------------------------------------------------------------
1.reallycrazy15b  |
              _at |
               1  |   .1512322   .0519221     2.91   0.004     .0494668    .2529977
               2  |   .1106691   .0339859     3.26   0.001     .0440581    .1772802
               3  |   .0781149   .0212896     3.67   0.000      .036388    .1198419
               4  |   .0528041   .0136244     3.88   0.000     .0261008    .0795073
               5  |   .0337266   .0100146     3.37   0.001     .0140983    .0533549
               6  |   .0197782   .0085136     2.32   0.020     .0030919    .0364645
               7  |   .0098788   .0074571     1.32   0.185    -.0047369    .0244946
               8  |   .0030528   .0062835     0.49   0.627    -.0092627    .0153683
               9  |  -.0015268   .0050346    -0.30   0.762    -.0113945    .0083409
              10  |  -.0045242   .0039065    -1.16   0.247    -.0121807    .0031324
              11  |  -.0064476    .003091    -2.09   0.037    -.0125057   -.0003894
-----------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recast(line) recastci(rline) addplot (histogram cincperc, bin(20) yaxis(2) below fre
> quency fcolor(none) lcolor(gs14)) title("General Deterrence Model: Marginal Effect of" "Leader B 
> Strong Madness Rep. on Initiation")

  Variables that uniquely identify margins: cincperc

. graph save Graph "GenDet_Strong.gph", replace
(note: file GenDet_Strong.gph not found)
(file GenDet_Strong.gph saved)

. margins, dydx(modcrazy15b) at(cincperc=(0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1)) noatlegend

Average marginal effects                        Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
dy/dx w.r.t. : 1.modcrazy15b

--------------------------------------------------------------------------------
               |            Delta-method
               |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
0.modcrazy15b  |  (base outcome)
---------------+----------------------------------------------------------------
1.modcrazy15b  |
           _at |
            1  |   .0072328    .007097     1.02   0.308    -.0066772    .0211427
            2  |   .0065035   .0058101     1.12   0.263     -.004884    .0178911
            3  |   .0057883   .0046176     1.25   0.210    -.0032621    .0148386
            4  |   .0050908   .0035398     1.44   0.150    -.0018471    .0120287
            5  |   .0044138   .0026189     1.69   0.092    -.0007191    .0095467
            6  |   .0037584   .0019534     1.92   0.054    -.0000703    .0075871
            7  |   .0031246   .0017211     1.82   0.069    -.0002487    .0064979
            8  |   .0025111   .0019792     1.27   0.205    -.0013681    .0063904
            9  |    .001916   .0025232     0.76   0.448    -.0030294    .0068614
           10  |   .0013369   .0031709     0.42   0.673    -.0048779    .0075517
           11  |   .0007716   .0038442     0.20   0.841    -.0067629     .008306
--------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recast(line) recastci(rline) addplot (histogram cincperc, bin(20) yaxis(2) below fre
> quency fcolor(none) lcolor(gs14)) title("General Deterrence Model: Marginal Effect of" "Leader B 
> Slight Madness Rep. on Initiation")

  Variables that uniquely identify margins: cincperc

. graph save Graph "GenDet_Slight.gph", replace
(note: file GenDet_Slight.gph not found)
(file GenDet_Slight.gph saved)

. 
. use "Crazy Leader MID Data", clear

. drop if tpopa<500 | tpopb<500
(19 observations deleted)

. eststo: probit recip reallycrazy15a##c.cincperc modcrazy15a##c.cincperc reallycrazy15b modcrazy15
> b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb dema demb jointdem landcontig distance in
> 1hostlev, cluster(ccodea)

note: cincperc omitted because of collinearity
Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -490.34334  
Iteration 2:   log pseudolikelihood = -490.15701  
Iteration 3:   log pseudolikelihood = -490.15671  
Iteration 4:   log pseudolikelihood = -490.15671  

Probit regression                               Number of obs     =        759
                                                Wald chi2(17)     =     173.30
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -490.15671               Pseudo R2         =     0.0552

                                            (Std. Err. adjusted for 114 clusters in ccodea)
-------------------------------------------------------------------------------------------
                          |               Robust
                    recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------------+----------------------------------------------------------------
         1.reallycrazy15a |  -1.901286   1.468193    -1.29   0.195    -4.778891    .9763186
                 cincperc |   .9816266   .5627201     1.74   0.081    -.1212846    2.084538
                          |
reallycrazy15a#c.cincperc |
                       1  |   4.690198   3.155157     1.49   0.137    -1.493796    10.87419
                          |
            1.modcrazy15a |   .9486594   .2947342     3.22   0.001     .3709911    1.526328
                 cincperc |          0  (omitted)
                          |
   modcrazy15a#c.cincperc |
                       1  |  -2.746034   .6095817    -4.50   0.000    -3.940792   -1.551276
                          |
           reallycrazy15b |  -.5607348   .2154047    -2.60   0.009    -.9829202   -.1385494
              modcrazy15b |  -.2000793   .1844862    -1.08   0.278    -.5616656    .1615071
     recentMIDs_byleadera |  -.0409278   .0951635    -0.43   0.667    -.2274449    .1455893
     recentMIDs_byleaderb |   .0919806    .102521     0.90   0.370    -.1089568     .292918
                    cinca |    -1.1212   1.881127    -0.60   0.551    -4.808141    2.565741
                    cincb |  -2.921586   1.541908    -1.89   0.058     -5.94367    .1004978
                     dema |  -.2095016   .2139572    -0.98   0.327    -.6288501    .2098468
                     demb |  -.0075298   .1463616    -0.05   0.959    -.2943933    .2793336
                 jointdem |  -.1445938    .283859    -0.51   0.610    -.7009471    .4117596
               landcontig |    .268214   .1443459     1.86   0.063    -.0146987    .5511268
                 distance |   .0163417   .0397388     0.41   0.681    -.0615448    .0942282
               in1hostlev |  -.0662364   .1449545    -0.46   0.648     -.350342    .2178693
                    _cons |  -.4321386   .6011291    -0.72   0.472     -1.61033    .7460528
-------------------------------------------------------------------------------------------
(est2 stored)

. margins, dydx(reallycrazy15a) at(cincperc=(0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1)) noatlegend

Average marginal effects                        Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
dy/dx w.r.t. : 1.reallycrazy15a

-----------------------------------------------------------------------------------
                  |            Delta-method
                  |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
0.reallycrazy15a  |  (base outcome)
------------------+----------------------------------------------------------------
1.reallycrazy15a  |
              _at |
               1  |   -.286689   .0866427    -3.31   0.001    -.4565055   -.1168725
               2  |  -.2850197   .1032468    -2.76   0.006    -.4873797   -.0826597
               3  |  -.2499576   .1403547    -1.78   0.075    -.5250478    .0251326
               4  |  -.1589136   .1473301    -1.08   0.281    -.4476753     .129848
               5  |  -.0092076   .0830576    -0.11   0.912    -.1719974    .1535822
               6  |   .1656267   .0570834     2.90   0.004     .0537453    .2775081
               7  |   .3137704   .1247767     2.51   0.012     .0692125    .5583283
               8  |   .4032876   .1330867     3.03   0.002     .1424423    .6641328
               9  |   .4373502   .1123038     3.89   0.000     .2172388    .6574616
              10  |   .4372994   .1035982     4.22   0.000     .2342506    .6403481
              11  |   .4217935   .1093629     3.86   0.000     .2074462    .6361408
-----------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recast(line) recastci(rline) addplot (histogram cincperc, bin(20) yaxis(2) below fre
> quency fcolor(none) lcolor(gs14)) title("Crisis Bargaining Model: Marginal Effect of" "Leader A S
> trong Madness Rep. on Reciprocation")

  Variables that uniquely identify margins: cincperc

. graph save Graph "Crisis_Strong.gph", replace
(note: file Crisis_Strong.gph not found)
(file Crisis_Strong.gph saved)

. margins, dydx(modcrazy15a) at(cincperc=(0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1)) noatlegend

Average marginal effects                        Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
dy/dx w.r.t. : 1.modcrazy15a

--------------------------------------------------------------------------------
               |            Delta-method
               |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
0.modcrazy15a  |  (base outcome)
---------------+----------------------------------------------------------------
1.modcrazy15a  |
           _at |
            1  |   .3397865   .1005894     3.38   0.001      .142635    .5369381
            2  |   .2442939   .0891485     2.74   0.006     .0695662    .4190217
            3  |   .1456611   .0776267     1.88   0.061    -.0064844    .2978066
            4  |     .04551   .0686468     0.66   0.507    -.0890352    .1800552
            5  |  -.0541263   .0646645    -0.84   0.403    -.1808663    .0726138
            6  |  -.1506433   .0661441    -2.28   0.023    -.2802834   -.0210031
            7  |  -.2414886   .0714427    -3.38   0.001    -.3815137   -.1014635
            8  |  -.3250864   .0790628    -4.11   0.000    -.4800467   -.1701262
            9  |  -.4010446   .0884755    -4.53   0.000    -.5744534   -.2276359
           10  |  -.4696261   .0994325    -4.72   0.000    -.6645103    -.274742
           11  |  -.5312491   .1115389    -4.76   0.000    -.7498612   -.3126369
--------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, recast(line) recastci(rline) addplot (histogram cincperc, bin(20) yaxis(2) below fre
> quency fcolor(none) lcolor(gs14)) title("Crisis Bargaining Model: Marginal Effect of" "Leader A S
> light Madness Rep. on Reciprocation")

  Variables that uniquely identify margins: cincperc

. graph save Graph "Crisis_Slight.gph", replace
(note: file Crisis_Slight.gph not found)
(file Crisis_Slight.gph saved)

. 
. // Note: A reallycrazy#modcrazy interaction or a three-way interaction are unnecessary and in fac
> t impossible to include because reallycrazy and modcrazy are mutually exclusive.
. 
. * Generage Figure 3 and Table A22
. gr combine GenDet_Strong.gph GenDet_Slight.gph Crisis_Strong.gph Crisis_Slight.gph

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A22: Interactions with Relative Capabilities") mtitles("Deterrence" "Crisis Bargaining")
(output written to appendix.rtf)

. eststo clear

. 
. * See which leaders are influencing this.
. tab leadera if modcrazy15a==1 & cincperc>.5

                                        |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
                            Ahmadinejad |          1        2.94        2.94
                           Ariel Sharon |          5       14.71       17.65
                         Chen Shui-bian |          1        2.94       20.59
                               Chretien |          1        2.94       23.53
                                 Howard |          3        8.82       32.35
                            Hugo Chavez |          1        2.94       35.29
                            Kim Jong-Il |          1        2.94       38.24
                                  Major |          1        2.94       41.18
                              Milosevic |          3        8.82       50.00
                             Mitterrand |          1        2.94       52.94
                                 Mugabe |          2        5.88       58.82
                               Museveni |          1        2.94       61.76
                              Netanyahu |          1        2.94       64.71
                                Qaddafi |          1        2.94       67.65
                                Yeltsin |         10       29.41       97.06
                             Yushchenko |          1        2.94      100.00
----------------------------------------+-----------------------------------
                                  Total |         34      100.00

. 
. 
. 
. 
. **************************** GENERAL DETERRENCE ROBUSTNESS CHECKS *******************************
> ***********
. 
. use "Dyadic Crazy Leader Data", clear

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. 
. * Table A7: Deterrence Regressions with Alternate Dummy Madness Measures and Dropping Outliers
. eststo: probit initMID reallycrazy5a modcrazy5a reallycrazy5b modcrazy5b recentMIDs_byleadera rec
> entMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs
>  peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2460.9798  
Iteration 2:   log pseudolikelihood = -2297.6003  
Iteration 3:   log pseudolikelihood = -2290.8595  
Iteration 4:   log pseudolikelihood = -2290.8033  
Iteration 5:   log pseudolikelihood = -2290.8033  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     844.20
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2290.8033               Pseudo R2         =     0.2466

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
       reallycrazy5a |   .8312067   .2695846     3.08   0.002     .3028306    1.359583
          modcrazy5a |   .0580029    .068431     0.85   0.397    -.0761193    .1921252
       reallycrazy5b |   1.082766   .2497992     4.33   0.000      .593169    1.572364
          modcrazy5b |   .2890802   .0697673     4.14   0.000     .1523389    .4258215
recentMIDs_byleadera |   .2322052   .0310527     7.48   0.000     .1713429    .2930675
recentMIDs_byleaderb |   .0415857    .031138     1.34   0.182    -.0194438    .1026151
               cinca |   1.842347   .7675123     2.40   0.016     .3380501    3.346643
               cincb |   1.239058   .5976177     2.07   0.038     .0677487    2.410367
            cincperc |   -.077183   .1718521    -0.45   0.653    -.4140069    .2596408
                dema |   .1198434   .0619444     1.93   0.053    -.0015654    .2412521
                demb |   .0889986   .0616192     1.44   0.149    -.0317728      .20977
            jointdem |  -.4994692   .1071067    -4.66   0.000    -.7093945   -.2895439
          landcontig |   .5443827   .0729234     7.47   0.000     .4014556    .6873099
            distance |  -.1223319   .0244681    -5.00   0.000    -.1702885   -.0743753
          dyadlength |   .6555423   .0792598     8.27   0.000     .5001959    .8108887
            peaceyrs |  -.0425499   .0040025   -10.63   0.000    -.0503948   -.0347051
         peaceyrs_sq |   .0005382   .0000742     7.25   0.000     .0003928    .0006836
        peaceyrs_cub |  -1.85e-06   3.52e-07    -5.27   0.000    -2.54e-06   -1.16e-06
               _cons |  -2.625379   .1498526   -17.52   0.000    -2.919085   -2.331674
--------------------------------------------------------------------------------------
(est1 stored)

. eststo: probit initMID reallycrazy20a modcrazy20a reallycrazy20b modcrazy20b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2456.4863  
Iteration 2:   log pseudolikelihood = -2290.0091  
Iteration 3:   log pseudolikelihood = -2283.2167  
Iteration 4:   log pseudolikelihood = -2283.1612  
Iteration 5:   log pseudolikelihood = -2283.1612  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     876.71
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2283.1612               Pseudo R2         =     0.2491

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy20a |   .2366655   .1820635     1.30   0.194    -.1201725    .5935035
         modcrazy20a |   .0846574   .0709837     1.19   0.233     -.054468    .2237829
      reallycrazy20b |   .9178945    .124713     7.36   0.000     .6734615    1.162328
         modcrazy20b |   .1162309    .078873     1.47   0.141    -.0383573     .270819
recentMIDs_byleadera |   .2330488   .0309118     7.54   0.000     .1724627    .2936348
recentMIDs_byleaderb |   .0513277   .0319547     1.61   0.108    -.0113024    .1139578
               cinca |   1.806718   .7723116     2.34   0.019     .2930156    3.320421
               cincb |   1.440206   .5792136     2.49   0.013     .3049683    2.575444
            cincperc |  -.0041302   .1698552    -0.02   0.981    -.3370403    .3287799
                dema |   .1086593   .0610906     1.78   0.075     -.011076    .2283946
                demb |   .1027202   .0615871     1.67   0.095    -.0179884    .2234287
            jointdem |  -.4952651   .1071881    -4.62   0.000      -.70535   -.2851802
          landcontig |    .539243   .0726217     7.43   0.000     .3969072    .6815788
            distance |  -.1205254   .0244856    -4.92   0.000    -.1685163   -.0725346
          dyadlength |   .6440426   .0782384     8.23   0.000     .4906982     .797387
            peaceyrs |   -.042048   .0040558   -10.37   0.000    -.0499972   -.0340988
         peaceyrs_sq |   .0005285   .0000752     7.03   0.000     .0003811     .000676
        peaceyrs_cub |  -1.81e-06   3.56e-07    -5.08   0.000    -2.51e-06   -1.11e-06
               _cons |  -2.661365   .1489411   -17.87   0.000    -2.953284   -2.369446
--------------------------------------------------------------------------------------
(est2 stored)

. eststo: probit initMID reallycrazy40a modcrazy40a reallycrazy40b modcrazy40b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2458.2214  
Iteration 2:   log pseudolikelihood = -2299.5796  
Iteration 3:   log pseudolikelihood = -2292.8998  
Iteration 4:   log pseudolikelihood = -2292.8444  
Iteration 5:   log pseudolikelihood = -2292.8444  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     841.82
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2292.8444               Pseudo R2         =     0.2459

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy40a |   .1275764   .1348652     0.95   0.344    -.1367545    .3919073
         modcrazy40a |   .0988313   .0729035     1.36   0.175    -.0440568    .2417195
      reallycrazy40b |   .6164906   .1047591     5.88   0.000     .4111666    .8218146
         modcrazy40b |   .1295276   .0891454     1.45   0.146    -.0451942    .3042494
recentMIDs_byleadera |   .2311485   .0309502     7.47   0.000     .1704872    .2918098
recentMIDs_byleaderb |   .0533492   .0325856     1.64   0.102    -.0105174    .1172158
               cinca |   1.769142   .7581269     2.33   0.020     .2832411    3.255044
               cincb |   1.261708   .5961191     2.12   0.034     .0933359     2.43008
            cincperc |  -.0321242   .1679241    -0.19   0.848    -.3612494    .2970009
                dema |   .1070522     .06161     1.74   0.082    -.0137013    .2278056
                demb |   .0954979   .0612035     1.56   0.119    -.0244588    .2154546
            jointdem |  -.4946175   .1070687    -4.62   0.000    -.7044682   -.2847668
          landcontig |   .5359183   .0727111     7.37   0.000     .3934072    .6784294
            distance |  -.1223609   .0244425    -5.01   0.000    -.1702673   -.0744546
          dyadlength |    .652229   .0791766     8.24   0.000     .4970457    .8074123
            peaceyrs |  -.0426903   .0040634   -10.51   0.000    -.0506544   -.0347261
         peaceyrs_sq |    .000541   .0000753     7.18   0.000     .0003934    .0006886
        peaceyrs_cub |  -1.86e-06   3.57e-07    -5.23   0.000    -2.56e-06   -1.16e-06
               _cons |  -2.639675   .1472623   -17.92   0.000    -2.928304   -2.351046
--------------------------------------------------------------------------------------
(est3 stored)

. eststo: probit initMID crazyscore_l1a crazyscore_l1b recentMIDs_byleadera recentMIDs_byleaderb ci
> nca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs peaceyrs_sq peaceyr
> s_cub if pol_rel==1 & crazyscore_l1b<=0.668460547924041, cluster(dyadid) // This is the 84th perc
> entile value

Iteration 0:   log pseudolikelihood = -2899.1114  
Iteration 1:   log pseudolikelihood = -2360.4919  
Iteration 2:   log pseudolikelihood = -2204.4263  
Iteration 3:   log pseudolikelihood =  -2198.183  
Iteration 4:   log pseudolikelihood =  -2198.134  
Iteration 5:   log pseudolikelihood =  -2198.134  

Probit regression                               Number of obs     =     62,077
                                                Wald chi2(16)     =     809.28
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2198.134               Pseudo R2         =     0.2418

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_l1a |   .1996611   .0842273     2.37   0.018     .0345786    .3647437
      crazyscore_l1b |   .9083623   .2991627     3.04   0.002     .3220142     1.49471
recentMIDs_byleadera |   .2395919     .03138     7.64   0.000     .1780883    .3010956
recentMIDs_byleaderb |   .0462223   .0319984     1.44   0.149    -.0164934     .108938
               cinca |   1.916105   .7627344     2.51   0.012     .4211732    3.411037
               cincb |    1.48257   .5868349     2.53   0.012     .3323949    2.632745
            cincperc |   .0417259   .1700809     0.25   0.806    -.2916266    .3750784
                dema |   .0905944   .0622919     1.45   0.146    -.0314955    .2126844
                demb |   .0913392   .0608194     1.50   0.133    -.0278646     .210543
            jointdem |  -.4588109   .1070665    -4.29   0.000    -.6686575   -.2489644
          landcontig |    .548565   .0732526     7.49   0.000     .4049925    .6921374
            distance |  -.1205744   .0255895    -4.71   0.000    -.1707289   -.0704199
          dyadlength |   .6270399   .0785158     7.99   0.000     .4731517    .7809281
            peaceyrs |  -.0420221   .0040452   -10.39   0.000    -.0499506   -.0340936
         peaceyrs_sq |   .0005267    .000075     7.02   0.000     .0003796    .0006737
        peaceyrs_cub |  -1.79e-06   3.55e-07    -5.05   0.000    -2.49e-06   -1.10e-06
               _cons |  -2.670985   .1470892   -18.16   0.000    -2.959275   -2.382696
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A7: Alternate Indicator Cutoffs and Dropping Outliers (Initiation Model)") mtitles("Top 
> 5% Indicator Cutoff" "Top 20% Indicator Cutoff" "Top 40% Indicator Cutoff" "Cont. Measure, Drop T
> op 16%") 
(output written to appendix.rtf)

. eststo clear

. 
. 
. * Table A8: Address Potential Regional and Time Bias
. // Region fixed effects
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub i.regiona i.regionb if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood =  -2431.308  
Iteration 2:   log pseudolikelihood = -2254.2823  
Iteration 3:   log pseudolikelihood = -2245.9041  
Iteration 4:   log pseudolikelihood = -2245.8136  
Iteration 5:   log pseudolikelihood = -2245.8136  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(26)     =     958.65
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2245.8136               Pseudo R2         =     0.2614

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1150532   .2073264     0.55   0.579    -.2912991    .5214054
         modcrazy15a |   .1062269   .0720417     1.47   0.140    -.0349722    .2474261
      reallycrazy15b |   .9178097   .1453784     6.31   0.000     .6328733    1.202746
         modcrazy15b |   .1336859   .0755616     1.77   0.077    -.0144121    .2817838
recentMIDs_byleadera |   .2623796   .0301067     8.71   0.000     .2033715    .3213877
recentMIDs_byleaderb |   .0992073   .0328611     3.02   0.003     .0348007    .1636138
               cinca |   1.521591   .8366252     1.82   0.069    -.1181646    3.161346
               cincb |  -.1201585   .6621697    -0.18   0.856    -1.417987     1.17767
            cincperc |   .4401943   .2170585     2.03   0.043     .0147673    .8656212
                dema |   .2002833   .0664443     3.01   0.003     .0700548    .3305118
                demb |   .1711182   .0720194     2.38   0.018     .0299629    .3122736
            jointdem |  -.5209587   .1047193    -4.97   0.000    -.7262047   -.3157127
          landcontig |   .4518912   .0698828     6.47   0.000     .3149235    .5888589
            distance |  -.1453848   .0226509    -6.42   0.000    -.1897798   -.1009898
          dyadlength |   .6707493   .0787037     8.52   0.000     .5164928    .8250059
            peaceyrs |   -.040669   .0040801    -9.97   0.000     -.048666   -.0326721
         peaceyrs_sq |   .0004919    .000079     6.23   0.000     .0003372    .0006467
        peaceyrs_cub |  -1.65e-06   3.79e-07    -4.35   0.000    -2.39e-06   -9.05e-07
                     |
             regiona |
                  2  |  -.3888607   .1192492    -3.26   0.001    -.6225849   -.1551366
                  3  |  -.1364168   .1377413    -0.99   0.322    -.4063848    .1335512
                  4  |  -.1618612   .1495602    -1.08   0.279    -.4549938    .1312713
                  5  |  -.3787257   .1607912    -2.36   0.019    -.6938705   -.0635808
                     |
             regionb |
                  2  |  -.1026552   .1188351    -0.86   0.388    -.3355677    .1302574
                  3  |   .0303682   .1306556     0.23   0.816    -.2257121    .2864486
                  4  |   .0376911   .1406891     0.27   0.789    -.2380544    .3134366
                  5  |   .3835715   .1621248     2.37   0.018     .0658129    .7013302
                     |
               _cons |  -2.685423    .193321   -13.89   0.000    -3.064325   -2.306521
--------------------------------------------------------------------------------------
(est1 stored)

. //Time Fixed Effects
. gen time=1 if year<1991
(692,706 missing values generated)

. replace time=2 if year>1990 & year<1995
(138,150 real changes made)

. replace time=3 if year>1994 & year<1999
(135,718 real changes made)

. replace time=4 if year>1998 & year<2003
(136,744 real changes made)

. replace time=5 if year>2002 & year<2007
(140,116 real changes made)

. replace time=6 if year>2006
(141,978 real changes made)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub i.time if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2451.1047  
Iteration 2:   log pseudolikelihood = -2279.7621  
Iteration 3:   log pseudolikelihood = -2271.9828  
Iteration 4:   log pseudolikelihood =  -2271.909  
Iteration 5:   log pseudolikelihood =  -2271.909  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(23)     =     905.61
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2271.909               Pseudo R2         =     0.2528

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1551812   .2130129     0.73   0.466    -.2623164    .5726788
         modcrazy15a |   .1222998   .0712058     1.72   0.086     -.017261    .2618606
      reallycrazy15b |   .9081792   .1388572     6.54   0.000     .6360242    1.180334
         modcrazy15b |   .1889924   .0763019     2.48   0.013     .0394434    .3385414
recentMIDs_byleadera |   .2381892   .0300026     7.94   0.000     .1793852    .2969932
recentMIDs_byleaderb |   .0558134   .0314146     1.78   0.076    -.0057582    .1173849
               cinca |   2.072166   .8048357     2.57   0.010     .4947174    3.649615
               cincb |   1.541705   .6204024     2.49   0.013      .325739    2.757672
            cincperc |  -.0136183   .1704476    -0.08   0.936    -.3476895    .3204529
                dema |   .1210718   .0607806     1.99   0.046      .001944    .2401996
                demb |   .1185205   .0618794     1.92   0.055    -.0027609    .2398019
            jointdem |  -.4941634   .1066338    -4.63   0.000    -.7031617    -.285165
          landcontig |   .5216734   .0721627     7.23   0.000     .3802371    .6631097
            distance |   -.120483   .0245398    -4.91   0.000    -.1685801   -.0723859
          dyadlength |   .6228242   .0777417     8.01   0.000     .4704533    .7751952
            peaceyrs |  -.0421859   .0040445   -10.43   0.000    -.0501129   -.0342589
         peaceyrs_sq |   .0005275   .0000748     7.06   0.000      .000381     .000674
        peaceyrs_cub |  -1.81e-06   3.54e-07    -5.12   0.000    -2.50e-06   -1.12e-06
                     |
                time |
                  2  |   -.119338   .0582545    -2.05   0.041    -.2335147   -.0051613
                  3  |   -.221196      .0614    -3.60   0.000    -.3415378   -.1008543
                  4  |  -.1193926   .0632218    -1.89   0.059     -.243305    .0045198
                  5  |  -.3568865   .0952322    -3.75   0.000    -.5435381   -.1702349
                  6  |  -.3764567    .094413    -3.99   0.000    -.5615028   -.1914106
                     |
               _cons |  -2.502276   .1519067   -16.47   0.000    -2.800007   -2.204544
--------------------------------------------------------------------------------------
(est2 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A8: Address Regional and Time Bias (Initiation Model)") mtitles("Region Fixed Effects" "
> Time Fixed Effects")
(output written to appendix.rtf)

. eststo clear 

. 
. * Table A9: Address Pro-Western Bias and Strategic Use of Madness Adjectives
. // Control for affinity with the US
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b affinity_us_a affini
> ty_us_b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcon
> tig distance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -2947.8786  
Iteration 1:   log pseudolikelihood = -2388.0414  
Iteration 2:   log pseudolikelihood = -2234.8786  
Iteration 3:   log pseudolikelihood =  -2228.549  
Iteration 4:   log pseudolikelihood = -2228.5008  
Iteration 5:   log pseudolikelihood = -2228.5008  

Probit regression                               Number of obs     =     57,730
                                                Wald chi2(20)     =     845.20
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2228.5008               Pseudo R2         =     0.2440

                                     (Std. Err. adjusted for 1,533 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1778662   .2132664     0.83   0.404    -.2401282    .5958607
         modcrazy15a |   .0793066   .0725637     1.09   0.274    -.0629156    .2215289
      reallycrazy15b |   .9195424   .1438627     6.39   0.000     .6375768    1.201508
         modcrazy15b |   .1348514   .0779518     1.73   0.084    -.0179313    .2876341
       affinity_us_a |   .0631302   .1010021     0.63   0.532    -.1348303    .2610907
       affinity_us_b |  -.0954615   .0902253    -1.06   0.290       -.2723    .0813769
recentMIDs_byleadera |   .2313345   .0323754     7.15   0.000     .1678798    .2947892
recentMIDs_byleaderb |   .0629725   .0318962     1.97   0.048     .0004572    .1254879
               cinca |   1.782642   .8084208     2.21   0.027     .1981668    3.367118
               cincb |   1.163514   .6543047     1.78   0.075    -.1188999    2.445927
            cincperc |   .1575174   .2327458     0.68   0.499     -.298656    .6136908
                dema |   .0896294   .0711807     1.26   0.208    -.0498823    .2291411
                demb |   .1397591    .064465     2.17   0.030       .01341    .2661082
            jointdem |  -.4958658   .1080586    -4.59   0.000    -.7076568   -.2840748
          landcontig |   .5310326   .0731595     7.26   0.000     .3876427    .6744225
            distance |  -.1213138   .0246936    -4.91   0.000    -.1697124   -.0729153
          dyadlength |    .654331   .0790616     8.28   0.000     .4993731     .809289
            peaceyrs |  -.0418667   .0040668   -10.29   0.000    -.0498374    -.033896
         peaceyrs_sq |   .0005254   .0000751     7.00   0.000     .0003782    .0006726
        peaceyrs_cub |  -1.80e-06   3.55e-07    -5.07   0.000    -2.49e-06   -1.10e-06
               _cons |  -2.749842   .1633854   -16.83   0.000    -3.070071   -2.429612
--------------------------------------------------------------------------------------
(est1 stored)

. // Use only non-US sources
. eststo: probit initMID reallycrazy15_nousa modcrazy15_nousa reallycrazy15_nousb modcrazy15_nousb 
> recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig dist
> ance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2457.2957  
Iteration 2:   log pseudolikelihood = -2294.9284  
Iteration 3:   log pseudolikelihood = -2288.1427  
Iteration 4:   log pseudolikelihood = -2288.0839  
Iteration 5:   log pseudolikelihood = -2288.0839  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     857.75
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2288.0839               Pseudo R2         =     0.2475

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
 reallycrazy15_nousa |   .3439695   .2013444     1.71   0.088    -.0506583    .7385973
    modcrazy15_nousa |   .1406986   .0743913     1.89   0.059    -.0051056    .2865028
 reallycrazy15_nousb |    .927496   .1507408     6.15   0.000     .6320495    1.222943
    modcrazy15_nousb |   .2144971   .0766193     2.80   0.005     .0643261    .3646681
recentMIDs_byleadera |   .2289961    .030659     7.47   0.000     .1689056    .2890867
recentMIDs_byleaderb |   .0488272   .0308803     1.58   0.114    -.0116971    .1093514
               cinca |     1.8287   .7752748     2.36   0.018     .3091895    3.348211
               cincb |   1.331068    .589557     2.26   0.024     .1755571    2.486578
            cincperc |  -.0082994   .1722819    -0.05   0.962    -.3459658     .329367
                dema |   .1132883   .0618744     1.83   0.067    -.0079833    .2345599
                demb |   .0901557   .0622073     1.45   0.147    -.0317683    .2120798
            jointdem |   -.506774   .1083408    -4.68   0.000     -.719118   -.2944299
          landcontig |   .5389573   .0729765     7.39   0.000     .3959259    .6819888
            distance |  -.1240678   .0245453    -5.05   0.000    -.1721756     -.07596
          dyadlength |   .6485908   .0781328     8.30   0.000     .4954533    .8017284
            peaceyrs |  -.0425338   .0040492   -10.50   0.000      -.05047   -.0345975
         peaceyrs_sq |   .0005389   .0000748     7.20   0.000     .0003922    .0006856
        peaceyrs_cub |  -1.86e-06   3.54e-07    -5.25   0.000    -2.55e-06   -1.16e-06
               _cons |  -2.649737   .1486456   -17.83   0.000    -2.941077   -2.358397
--------------------------------------------------------------------------------------
(est2 stored)

. // Drop English-Speaking Western Countries
. preserve

. drop if ccodea<21 | ccodea==200 | ccodea==205 | ccodea==900 | ccodea==920 | ccodeb<21 | ccodeb==2
> 00 | ccodeb==205 | ccodeb==900 | ccodeb==920
(61,868 observations deleted)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -2469.6012  
Iteration 1:   log pseudolikelihood = -1990.6112  
Iteration 2:   log pseudolikelihood = -1848.7385  
Iteration 3:   log pseudolikelihood = -1831.2947  
Iteration 4:   log pseudolikelihood = -1830.5414  
Iteration 5:   log pseudolikelihood = -1830.5402  
Iteration 6:   log pseudolikelihood = -1830.5402  

Probit regression                               Number of obs     =     45,980
                                                Wald chi2(18)     =     545.44
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1830.5402               Pseudo R2         =     0.2588

                                     (Std. Err. adjusted for 1,197 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .2189693   .2218328     0.99   0.324    -.2158151    .6537536
         modcrazy15a |  -.0474528   .0994072    -0.48   0.633    -.2422873    .1473817
      reallycrazy15b |   .7407553   .1921576     3.85   0.000     .3641334    1.117377
         modcrazy15b |   .0696233   .1127358     0.62   0.537    -.1513349    .2905815
recentMIDs_byleadera |   .2449125   .0359957     6.80   0.000     .1743622    .3154628
recentMIDs_byleaderb |   .0041959   .0396139     0.11   0.916     -.073446    .0818378
               cinca |   1.901265   1.078068     1.76   0.078    -.2117101    4.014239
               cincb |   1.607379   .7930532     2.03   0.043     .0530229    3.161734
            cincperc |    .109517   .3919589     0.28   0.780    -.6587082    .8777422
                dema |   .0436777   .0689433     0.63   0.526    -.0914488    .1788041
                demb |   .0651666    .070834     0.92   0.358    -.0736654    .2039986
            jointdem |  -.4013474   .1310482    -3.06   0.002    -.6581973   -.1444976
          landcontig |   .4382405   .0738224     5.94   0.000     .2935512    .5829297
            distance |  -.2419463   .0399886    -6.05   0.000    -.3203224   -.1635702
          dyadlength |   .5640743   .0849082     6.64   0.000     .3976573    .7304913
            peaceyrs |  -.0384949   .0049018    -7.85   0.000    -.0481024   -.0288875
         peaceyrs_sq |   .0004807   .0001064     4.52   0.000     .0002721    .0006893
        peaceyrs_cub |  -1.68e-06   5.53e-07    -3.04   0.002    -2.76e-06   -5.96e-07
               _cons |  -2.440712   .2361757   -10.33   0.000    -2.903608   -1.977816
--------------------------------------------------------------------------------------
Note: 42 failures and 0 successes completely determined.
(est3 stored)

. restore

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A9: Address Pro-Western Bias and Strategic Use of Madness Adjectives (Initiation Model)"
> ) mtitles("Control for US Affinity" "Only Non-US Sources" "Drop English-Speaking Western Countrie
> s")
(output written to appendix.rtf)

. eststo clear 

. 
. 
. * Table A10: Control for and Match on Other Characteristics Associated with Perceived Madness and
>  Control for Reputation.
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b yrs_in_ofc_l1b recen
> tMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance 
> dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2457.2531  
Iteration 2:   log pseudolikelihood = -2290.7156  
Iteration 3:   log pseudolikelihood = -2284.0348  
Iteration 4:   log pseudolikelihood = -2283.9827  
Iteration 5:   log pseudolikelihood = -2283.9827  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(19)     =     881.77
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2283.9827               Pseudo R2         =     0.2488

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1664463   .2130412     0.78   0.435    -.2511068    .5839994
         modcrazy15a |   .0995949   .0707777     1.41   0.159    -.0391268    .2383166
      reallycrazy15b |   .9556517   .1365161     7.00   0.000     .6880851    1.223218
         modcrazy15b |   .1743578   .0750774     2.32   0.020     .0272088    .3215068
      yrs_in_ofc_l1b |  -.0111911   .0050898    -2.20   0.028     -.021167   -.0012153
recentMIDs_byleadera |   .2314842   .0308826     7.50   0.000     .1709554     .292013
recentMIDs_byleaderb |   .0469975   .0314104     1.50   0.135    -.0145657    .1085608
               cinca |   1.719965   .7690596     2.24   0.025     .2126359    3.227294
               cincb |   1.284103   .5877076     2.18   0.029     .1322174    2.435989
            cincperc |  -.0254603   .1694893    -0.15   0.881    -.3576533    .3067326
                dema |   .0987991   .0607418     1.63   0.104    -.0202526    .2178508
                demb |   .0715122   .0634107     1.13   0.259    -.0527705    .1957949
            jointdem |  -.4839122   .1064153    -4.55   0.000    -.6924823    -.275342
          landcontig |   .5326717   .0727842     7.32   0.000     .3900173    .6753261
            distance |  -.1190164   .0243095    -4.90   0.000    -.1666622   -.0713706
          dyadlength |   .6392508   .0777454     8.22   0.000     .4868725     .791629
            peaceyrs |    -.04184   .0040407   -10.35   0.000    -.0497596   -.0339203
         peaceyrs_sq |   .0005226   .0000749     6.98   0.000     .0003758    .0006695
        peaceyrs_cub |  -1.79e-06   3.54e-07    -5.05   0.000    -2.48e-06   -1.09e-06
               _cons |  -2.558418    .152551   -16.77   0.000    -2.857413   -2.259424
--------------------------------------------------------------------------------------
(est1 stored)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1 & yrs_in_ofc_l1b>4, cluster(dyadid)

Iteration 0:   log pseudolikelihood =  -1680.227  
Iteration 1:   log pseudolikelihood = -1336.6883  
Iteration 2:   log pseudolikelihood = -1244.4441  
Iteration 3:   log pseudolikelihood = -1239.9704  
Iteration 4:   log pseudolikelihood = -1239.9246  
Iteration 5:   log pseudolikelihood = -1239.9246  

Probit regression                               Number of obs     =     32,962
                                                Wald chi2(18)     =     559.19
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1239.9246               Pseudo R2         =     0.2620

                                     (Std. Err. adjusted for 1,543 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .2795585    .255455     1.09   0.274    -.2211241    .7802411
         modcrazy15a |   .0381299   .0971804     0.39   0.695    -.1523402       .2286
      reallycrazy15b |   .7301693   .1675079     4.36   0.000     .4018597    1.058479
         modcrazy15b |   .1798181   .0945654     1.90   0.057    -.0055266    .3651628
recentMIDs_byleadera |   .2575974   .0377006     6.83   0.000     .1837057    .3314892
recentMIDs_byleaderb |   .1351816    .043268     3.12   0.002     .0503778    .2199854
               cinca |    .748866   .9979031     0.75   0.453    -1.206988     2.70472
               cincb |   1.285207   .9467724     1.36   0.175     -.570433    3.140846
            cincperc |  -.5056402   .2492976    -2.03   0.043    -.9942545    -.017026
                dema |   .1533871   .0773473     1.98   0.047     .0017892    .3049849
                demb |   .2173329    .090922     2.39   0.017     .0391291    .3955368
            jointdem |  -.6047404   .1575021    -3.84   0.000    -.9134388   -.2960421
          landcontig |   .5390197   .0953248     5.65   0.000     .3521865    .7258528
            distance |  -.1245551     .03182    -3.91   0.000    -.1869211   -.0621891
          dyadlength |   .6638249   .1226916     5.41   0.000     .4233538    .9042959
            peaceyrs |  -.0502781   .0058325    -8.62   0.000    -.0617096   -.0388466
         peaceyrs_sq |    .000687   .0001208     5.69   0.000     .0004502    .0009238
        peaceyrs_cub |  -2.52e-06   6.26e-07    -4.03   0.000    -3.75e-06   -1.30e-06
               _cons |  -2.445387   .2038556   -12.00   0.000    -2.844937   -2.045837
--------------------------------------------------------------------------------------
(est2 stored)

. preserve

. drop if reallycrazy15b==. | modcrazy15b==. | yrs_in_ofc_l1b==. | rebel_l1b==. | personalist_l1b==
> .
(427,385 observations deleted)

. gen anycrazyb=(reallycrazy15b==1 | modcrazy15b==1)

. drop if pol_rel!=1
(343,020 observations deleted)

. cem  westb (.5) personalist_l1b (.5) recentMIDs_stateb (2.5) rebel_l1b (.5) yrs_in_ofc_l1b (4.5 8
> .5), tr(anycrazyb)

Matching Summary:
-----------------
Number of strata: 35
Number of matched strata: 19

               0      1
      All  41283   4658
  Matched  36534   4658
Unmatched   4749      0


Multivariate L1 distance: .92968678

Univariate imbalance:

                         L1      mean       min       25%       50%       75%       max
            westb   4.6e-14  -7.1e-14         0         0         0         0         0
  personalist_l1b   1.1e-14  -4.5e-15         0         0         0         0         0
recentMIDs_stateb    .46711    .13727         0        .6       -.2       -.4      -3.4
        rebel_l1b   1.1e-13   7.8e-15         0         0         0         0         0
   yrs_in_ofc_l1b    .22712    .20169         0         0         0         0         0

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1 [iweight=cem_weights], cluster(dyadid)

Iteration 0:   log pseudolikelihood = -2013.1975  
Iteration 1:   log pseudolikelihood = -1596.3046  
Iteration 2:   log pseudolikelihood = -1474.2649  
Iteration 3:   log pseudolikelihood = -1469.5763  
Iteration 4:   log pseudolikelihood = -1469.5518  
Iteration 5:   log pseudolikelihood = -1469.5518  

Probit regression                               Number of obs     =     35,396
                                                Wald chi2(18)     =     533.75
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1469.5518               Pseudo R2         =     0.2700

                                     (Std. Err. adjusted for 1,513 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |  -.7802374   .3041393    -2.57   0.010    -1.376339   -.1841354
         modcrazy15a |   .2058837   .1500034     1.37   0.170    -.0881175    .4998849
      reallycrazy15b |    .737268   .1436165     5.13   0.000     .4557849    1.018751
         modcrazy15b |   .0627991   .0865554     0.73   0.468    -.1068463    .2324445
recentMIDs_byleadera |   .3022565   .0539052     5.61   0.000     .1966042    .4079087
recentMIDs_byleaderb |   .0182246   .0431361     0.42   0.673    -.0663206    .1027698
               cinca |   3.048973   1.336321     2.28   0.023     .4298318    5.668114
               cincb |    1.07368   .8286009     1.30   0.195    -.5503477    2.697708
            cincperc |  -.0245568   .2321355    -0.11   0.916     -.479534    .4304204
                dema |   .1159939   .1394318     0.83   0.405    -.1572874    .3892753
                demb |   .1057285    .104416     1.01   0.311     -.098923    .3103801
            jointdem |   -.695741   .1924543    -3.62   0.000    -1.072945   -.3185375
          landcontig |    .500098   .1216453     4.11   0.000     .2616776    .7385183
            distance |  -.0560368   .0349079    -1.61   0.108     -.124455    .0123815
          dyadlength |   .6246904   .2116615     2.95   0.003     .2098415    1.039539
            peaceyrs |  -.0505044   .0087993    -5.74   0.000    -.0677508   -.0332581
         peaceyrs_sq |   .0006748   .0001308     5.16   0.000     .0004185    .0009311
        peaceyrs_cub |  -2.38e-06   5.22e-07    -4.55   0.000    -3.40e-06   -1.35e-06
               _cons |  -2.643671   .2809785    -9.41   0.000    -3.194379   -2.092963
--------------------------------------------------------------------------------------
(est3 stored)

. restore

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recent_bluffsa recen
> t_bluffsb recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landc
> ontig distance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2450.6617  
Iteration 2:   log pseudolikelihood = -2281.0922  
Iteration 3:   log pseudolikelihood = -2273.6632  
Iteration 4:   log pseudolikelihood =  -2273.591  
Iteration 5:   log pseudolikelihood =  -2273.591  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(20)     =     884.06
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2273.591               Pseudo R2         =     0.2523

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .0884329   .2099951     0.42   0.674    -.3231499    .5000157
         modcrazy15a |   .0823088   .0718731     1.15   0.252    -.0585599    .2231775
      reallycrazy15b |   .9036571   .1381274     6.54   0.000     .6329324    1.174382
         modcrazy15b |   .1522673   .0757309     2.01   0.044     .0038375    .3006972
      recent_bluffsa |  -.4043094   .0955953    -4.23   0.000    -.5916727    -.216946
      recent_bluffsb |  -.0482856   .0945722    -0.51   0.610    -.2336438    .1370726
recentMIDs_byleadera |    .389839   .0427192     9.13   0.000     .3061109     .473567
recentMIDs_byleaderb |    .070226   .0479731     1.46   0.143    -.0237996    .1642515
               cinca |   2.807774   .8366735     3.36   0.001     1.167924    4.447624
               cincb |   1.564589   .6530133     2.40   0.017     .2847062    2.844471
            cincperc |   .0443431   .1760743     0.25   0.801    -.3007562    .3894424
                dema |   .0959616   .0610231     1.57   0.116    -.0236415    .2155647
                demb |   .1188154   .0614393     1.93   0.053    -.0016034    .2392341
            jointdem |  -.5130129   .1090469    -4.70   0.000    -.7267409   -.2992849
          landcontig |   .5372349   .0725883     7.40   0.000     .3949644    .6795053
            distance |  -.1285668   .0246335    -5.22   0.000    -.1768477    -.080286
          dyadlength |   .6458185    .080014     8.07   0.000     .4889939    .8026431
            peaceyrs |  -.0419156   .0039544   -10.60   0.000    -.0496661   -.0341652
         peaceyrs_sq |   .0005309    .000073     7.27   0.000     .0003878    .0006741
        peaceyrs_cub |  -1.83e-06   3.45e-07    -5.31   0.000    -2.51e-06   -1.15e-06
               _cons |  -2.694846   .1544724   -17.45   0.000    -2.997606   -2.392086
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A10: Address Potentially Confounding Leader and Country Characteristics (Initiation Mode
> l)") mtitles("Control for Time in Office" "Drop Leaders in Office <5 Years" "Matched Sample" "Con
> trol for Reputation")
(output written to appendix.rtf)

. eststo clear 

. 
. * Table A11: Other Changes to Madness Measure and Comparison with Tough Measure
. // Control for tough measure
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b reallytough15b modto
> ugh15b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcont
> ig distance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2459.4166  
Iteration 2:   log pseudolikelihood = -2293.6717  
Iteration 3:   log pseudolikelihood = -2286.9782  
Iteration 4:   log pseudolikelihood = -2286.9246  
Iteration 5:   log pseudolikelihood = -2286.9246  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(20)     =     865.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2286.9246               Pseudo R2         =     0.2479

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1617471   .2102225     0.77   0.442    -.2502814    .5737757
         modcrazy15a |   .0970527   .0705438     1.38   0.169    -.0412106     .235316
      reallycrazy15b |   .8976798   .1373151     6.54   0.000     .6285471    1.166812
         modcrazy15b |   .1406708    .074869     1.88   0.060    -.0060698    .2874113
      reallytough15b |   .0436911   .1361672     0.32   0.748    -.2231917    .3105739
         modtough15b |   .0537705   .0762426     0.71   0.481    -.0956623    .2032033
recentMIDs_byleadera |   .2318957   .0308527     7.52   0.000     .1714255     .292366
recentMIDs_byleaderb |   .0422728   .0335181     1.26   0.207    -.0234214     .107967
               cinca |   1.793454   .7705097     2.33   0.020     .2832824    3.303625
               cincb |   1.372836   .5930154     2.32   0.021     .2105476    2.535125
            cincperc |  -.0340936   .1760406    -0.19   0.846     -.379127    .3109397
                dema |   .1038911   .0611733     1.70   0.089    -.0160064    .2237885
                demb |   .0976474   .0613731     1.59   0.112    -.0226417    .2179365
            jointdem |  -.4875478   .1065884    -4.57   0.000    -.6964572   -.2786385
          landcontig |   .5415173   .0733069     7.39   0.000     .3978383    .6851963
            distance |  -.1213897   .0243112    -4.99   0.000    -.1690389   -.0737406
          dyadlength |   .6306809    .078057     8.08   0.000     .4776921    .7836697
            peaceyrs |   -.042451   .0040546   -10.47   0.000    -.0503979   -.0345041
         peaceyrs_sq |   .0005352   .0000751     7.13   0.000      .000388    .0006824
        peaceyrs_cub |  -1.84e-06   3.55e-07    -5.18   0.000    -2.54e-06   -1.14e-06
               _cons |  -2.627565   .1514431   -17.35   0.000    -2.924388   -2.330742
--------------------------------------------------------------------------------------
(est1 stored)

. // Use only words used in foreign policy or general context (dropping domestic context).
. eststo: probit initMID reallycrazy15_fpa modcrazy15_fpa reallycrazy15_fpb modcrazy15_fpb recentMI
> Ds_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dya
> dlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2461.3986  
Iteration 2:   log pseudolikelihood = -2296.0452  
Iteration 3:   log pseudolikelihood = -2289.4092  
Iteration 4:   log pseudolikelihood = -2289.3563  
Iteration 5:   log pseudolikelihood = -2289.3563  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     862.98
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2289.3563               Pseudo R2         =     0.2471

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
   reallycrazy15_fpa |   .1647784   .2093307     0.79   0.431    -.2455022     .575059
      modcrazy15_fpa |   .1366878   .0706281     1.94   0.053    -.0017408    .2751163
   reallycrazy15_fpb |   .9026774   .1445983     6.24   0.000     .6192699    1.186085
      modcrazy15_fpb |   .1945198   .0773456     2.51   0.012     .0429252    .3461144
recentMIDs_byleadera |   .2272984   .0308192     7.38   0.000     .1668938     .287703
recentMIDs_byleaderb |   .0444988    .031633     1.41   0.160    -.0175007    .1064984
               cinca |   1.800876   .7740382     2.33   0.020     .2837885    3.317963
               cincb |   1.397461   .5828906     2.40   0.017     .2550161    2.539905
            cincperc |  -.0144637   .1697178    -0.09   0.932    -.3471045    .3181771
                dema |   .1046822   .0612191     1.71   0.087    -.0153049    .2246694
                demb |    .098512   .0616811     1.60   0.110    -.0223806    .2194047
            jointdem |  -.4889363   .1065868    -4.59   0.000    -.6978427   -.2800299
          landcontig |   .5389455   .0727147     7.41   0.000     .3964273    .6814636
            distance |  -.1214744   .0243387    -4.99   0.000    -.1691774   -.0737713
          dyadlength |   .6324211   .0771776     8.19   0.000     .4811558    .7836864
            peaceyrs |  -.0425614   .0040592   -10.49   0.000    -.0505173   -.0346055
         peaceyrs_sq |   .0005364   .0000757     7.09   0.000      .000388    .0006848
        peaceyrs_cub |  -1.84e-06   3.60e-07    -5.12   0.000    -2.55e-06   -1.14e-06
               _cons |  -2.631713   .1480629   -17.77   0.000    -2.921911   -2.341515
--------------------------------------------------------------------------------------
(est2 stored)

. // Averaging over different time periods
. eststo: probit initMID reallycrazy15_avg5a modcrazy15_avg5a reallycrazy15_avg5b modcrazy15_avg5b 
> recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig dist
> ance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2460.9382  
Iteration 2:   log pseudolikelihood = -2300.6936  
Iteration 3:   log pseudolikelihood = -2294.2606  
Iteration 4:   log pseudolikelihood = -2294.2119  
Iteration 5:   log pseudolikelihood = -2294.2119  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     839.95
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2294.2119               Pseudo R2         =     0.2455

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
 reallycrazy15_avg5a |   .1500738   .1431754     1.05   0.295    -.1305449    .4306925
    modcrazy15_avg5a |  -.0032697   .0643086    -0.05   0.959    -.1293122    .1227729
 reallycrazy15_avg5b |   .6773258   .1523561     4.45   0.000     .3787133    .9759383
    modcrazy15_avg5b |   .1553508   .0713794     2.18   0.030     .0154499    .2952518
recentMIDs_byleadera |   .2380978   .0321562     7.40   0.000     .1750728    .3011228
recentMIDs_byleaderb |    .039031   .0329021     1.19   0.236     -.025456     .103518
               cinca |   1.815783    .763897     2.38   0.017     .3185727    3.312994
               cincb |   1.496742   .5821017     2.57   0.010     .3558436     2.63764
            cincperc |   -.063948   .1731436    -0.37   0.712    -.4033033    .2754073
                dema |   .1158931   .0626162     1.85   0.064    -.0068324    .2386186
                demb |   .1152746   .0626538     1.84   0.066    -.0075247    .2380739
            jointdem |  -.4947905   .1062886    -4.66   0.000    -.7031124   -.2864686
          landcontig |   .5402881   .0733306     7.37   0.000     .3965627    .6840134
            distance |  -.1200957     .02455    -4.89   0.000    -.1682128   -.0719785
          dyadlength |    .638579   .0781651     8.17   0.000     .4853782    .7917798
            peaceyrs |  -.0417387   .0040463   -10.32   0.000    -.0496694    -.033808
         peaceyrs_sq |   .0005237   .0000752     6.96   0.000     .0003763    .0006712
        peaceyrs_cub |  -1.79e-06   3.57e-07    -5.03   0.000    -2.49e-06   -1.09e-06
               _cons |  -2.636886   .1520692   -17.34   0.000    -2.934936   -2.338836
--------------------------------------------------------------------------------------
(est3 stored)

. eststo: probit initMID reallycrazy15_avg10a modcrazy15_avg10a reallycrazy15_avg10b modcrazy15_avg
> 10b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig 
> distance dyadlength peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2457.1795  
Iteration 2:   log pseudolikelihood = -2296.0897  
Iteration 3:   log pseudolikelihood = -2289.4344  
Iteration 4:   log pseudolikelihood = -2289.3826  
Iteration 5:   log pseudolikelihood = -2289.3826  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     853.25
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2289.3826               Pseudo R2         =     0.2471

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
reallycrazy15_avg10a |   .0849089   .1395341     0.61   0.543    -.1885729    .3583906
   modcrazy15_avg10a |  -.0149515   .0610389    -0.24   0.806    -.1345855    .1046825
reallycrazy15_avg10b |   .7191828   .1392354     5.17   0.000     .4462864    .9920793
   modcrazy15_avg10b |   .0996872   .0737569     1.35   0.177    -.0448737    .2442481
recentMIDs_byleadera |   .2415801   .0322895     7.48   0.000     .1782938    .3048664
recentMIDs_byleaderb |   .0436354    .034021     1.28   0.200    -.0230444    .1103153
               cinca |   1.804375    .750496     2.40   0.016     .3334294     3.27532
               cincb |   1.549453   .5783242     2.68   0.007     .4159585    2.682948
            cincperc |  -.0406551   .1746891    -0.23   0.816    -.3830394    .3017293
                dema |   .1140027   .0628489     1.81   0.070    -.0091789    .2371842
                demb |     .11868   .0625379     1.90   0.058     -.003892     .241252
            jointdem |  -.4915701   .1059048    -4.64   0.000    -.6991398   -.2840005
          landcontig |   .5372526   .0737101     7.29   0.000     .3927835    .6817217
            distance |  -.1193961   .0245671    -4.86   0.000    -.1675466   -.0712455
          dyadlength |   .6380262   .0787324     8.10   0.000     .4837135     .792339
            peaceyrs |  -.0417051   .0040684   -10.25   0.000    -.0496791   -.0337311
         peaceyrs_sq |   .0005224    .000076     6.88   0.000     .0003735    .0006713
        peaceyrs_cub |  -1.79e-06   3.61e-07    -4.95   0.000    -2.49e-06   -1.08e-06
               _cons |  -2.650348   .1514742   -17.50   0.000    -2.947232   -2.353465
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A11: Adjustments to the Madness Measure (Initiation Model)") mtitles("Compare to Tough S
> core" "Drop Words Used outside FP Context" "5-Year Average" "10-Year Average")
(output written to appendix.rtf)

. eststo clear

. 
. * Table A12: Change Sample and DV
. // Sample of all dyads
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -5715.9655  
Iteration 1:   log pseudolikelihood = -4107.3476  
Iteration 2:   log pseudolikelihood = -3735.2467  
Iteration 3:   log pseudolikelihood = -3675.0789  
Iteration 4:   log pseudolikelihood = -3673.8387  
Iteration 5:   log pseudolikelihood = -3673.8367  
Iteration 6:   log pseudolikelihood = -3673.8367  

Probit regression                               Number of obs     =    605,264
                                                Wald chi2(18)     =    1736.29
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3673.8367               Pseudo R2         =     0.3573

                                    (Std. Err. adjusted for 14,024 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1745581   .1308792     1.33   0.182    -.0819603    .4310766
         modcrazy15a |   .2224781   .0623497     3.57   0.000     .1002749    .3446812
      reallycrazy15b |   .8741917   .0772674    11.31   0.000     .7227503    1.025633
         modcrazy15b |   .2777769   .0668074     4.16   0.000     .1468368    .4087171
recentMIDs_byleadera |   .3088692   .0260802    11.84   0.000     .2577528    .3599855
recentMIDs_byleaderb |   .1210273   .0268658     4.50   0.000     .0683713    .1736832
               cinca |   3.244863   .7433079     4.37   0.000     1.788007     4.70172
               cincb |   2.733595   .6128801     4.46   0.000     1.532373    3.934818
            cincperc |  -.0113464   .1310933    -0.09   0.931    -.2682846    .2455918
                dema |   .1700396   .0436859     3.89   0.000     .0844168    .2556625
                demb |   .0883345   .0481195     1.84   0.066     -.005978     .182647
            jointdem |  -.4394612   .0890242    -4.94   0.000    -.6139455    -.264977
          landcontig |   .9156938   .0613526    14.93   0.000      .795445    1.035943
            distance |  -.1341967   .0188755    -7.11   0.000    -.1711921   -.0972013
          dyadlength |   .5829896   .0653078     8.93   0.000     .4549886    .7109906
            peaceyrs |  -.0397027   .0035773   -11.10   0.000     -.046714   -.0326914
         peaceyrs_sq |   .0005653   .0000769     7.35   0.000     .0004145    .0007161
        peaceyrs_cub |  -2.15e-06   4.01e-07    -5.37   0.000    -2.94e-06   -1.37e-06
               _cons |  -3.155034   .1171377   -26.93   0.000     -3.38462   -2.925449
--------------------------------------------------------------------------------------
(est1 stored)

. // Only dyads that have had a MID recently
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if recentMID_nar==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood =  -2080.785  
Iteration 1:   log pseudolikelihood =  -1846.156  
Iteration 2:   log pseudolikelihood = -1826.5805  
Iteration 3:   log pseudolikelihood =  -1826.368  
Iteration 4:   log pseudolikelihood = -1826.3676  
Iteration 5:   log pseudolikelihood = -1826.3676  

Probit regression                               Number of obs     =     11,092
                                                Wald chi2(18)     =     442.85
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1826.3676               Pseudo R2         =     0.1223

                                       (Std. Err. adjusted for 363 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |  -.2599241   .2010611    -1.29   0.196    -.6539965    .1341484
         modcrazy15a |   .0022894   .0764953     0.03   0.976    -.1476386    .1522174
      reallycrazy15b |   .5195482   .1274599     4.08   0.000     .2697314     .769365
         modcrazy15b |   .1345894   .0797969     1.69   0.092    -.0218096    .2909884
recentMIDs_byleadera |   .1835335   .0408283     4.50   0.000     .1035116    .2635554
recentMIDs_byleaderb |  -.0291943   .0375901    -0.78   0.437    -.1028696    .0444809
               cinca |   2.633435   .9741123     2.70   0.007     .7242097     4.54266
               cincb |   1.701567   .6068429     2.80   0.005     .5121766    2.890957
            cincperc |  -.1322047   .1959819    -0.67   0.500    -.5163222    .2519127
                dema |   .0686939   .0607517     1.13   0.258    -.0503773    .1877651
                demb |  -.0149545    .074107    -0.20   0.840    -.1602015    .1302924
            jointdem |  -.1567431   .1150866    -1.36   0.173    -.3823088    .0688225
          landcontig |   .4070924   .0684454     5.95   0.000     .2729419    .5412429
            distance |  -.0638314    .024754    -2.58   0.010    -.1123484   -.0153144
          dyadlength |   .6607986   .0901791     7.33   0.000     .4840509    .8375464
            peaceyrs |  -.1650139   .0395904    -4.17   0.000    -.2426097   -.0874182
         peaceyrs_sq |   .0164976    .009079     1.82   0.069     -.001297    .0342922
        peaceyrs_cub |  -.0007493   .0005252    -1.43   0.154    -.0017786      .00028
               _cons |   -2.19672   .1614299   -13.61   0.000    -2.513117   -1.880323
--------------------------------------------------------------------------------------
(est2 stored)

. // Forceful and Fatal MID dependent variables
. eststo: probit initForceMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byle
> adera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength
>  peaceyrs_for peaceyrs_for_sq peaceyrs_for_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -1958.9188  
Iteration 1:   log pseudolikelihood =  -1648.636  
Iteration 2:   log pseudolikelihood = -1518.4405  
Iteration 3:   log pseudolikelihood = -1512.1375  
Iteration 4:   log pseudolikelihood = -1511.6966  
Iteration 5:   log pseudolikelihood = -1511.6935  
Iteration 6:   log pseudolikelihood = -1511.6935  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     665.49
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1511.6935               Pseudo R2         =     0.2283

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
        initForceMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |  -.0113656   .2522498    -0.05   0.964    -.5057662     .483035
         modcrazy15a |   .0216274   .0930018     0.23   0.816    -.1606528    .2039077
      reallycrazy15b |   .7889702   .1499883     5.26   0.000     .4949986    1.082942
         modcrazy15b |   .0888988   .0957276     0.93   0.353    -.0987239    .2765215
recentMIDs_byleadera |   .2276222   .0317067     7.18   0.000     .1654781    .2897662
recentMIDs_byleaderb |   .0460312   .0344397     1.34   0.181    -.0214694    .1135318
               cinca |   .1779231   .7125713     0.25   0.803    -1.218691    1.574537
               cincb |   .7540968   .6513465     1.16   0.247    -.5225188    2.030712
            cincperc |  -.0121916   .1874387    -0.07   0.948    -.3795647    .3551816
                dema |   .0763626    .066931     1.14   0.254    -.0548197     .207545
                demb |  -.0467747    .072378    -0.65   0.518     -.188633    .0950836
            jointdem |  -.3522595   .1206166    -2.92   0.003    -.5886637   -.1158552
          landcontig |   .5938297   .0783268     7.58   0.000     .4403121    .7473473
            distance |   -.080873    .024134    -3.35   0.001    -.1281746   -.0335713
          dyadlength |   .5282023   .0994231     5.31   0.000     .3333367     .723068
        peaceyrs_for |  -.0490067   .0061337    -7.99   0.000    -.0610286   -.0369848
     peaceyrs_for_sq |   .0007965   .0001427     5.58   0.000     .0005167    .0010762
    peaceyrs_for_cub |  -3.47e-06   8.38e-07    -4.14   0.000    -5.11e-06   -1.82e-06
               _cons |   -2.69619   .1764301   -15.28   0.000    -3.041986   -2.350393
--------------------------------------------------------------------------------------
Note: 401 failures and 0 successes completely determined.
(est3 stored)

. eststo: probit initFatalMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byle
> adera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength
>  peaceyrs_fat peaceyrs_fat_sq peaceyrs_fat_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -1590.6908  
Iteration 1:   log pseudolikelihood = -1367.0583  
Iteration 2:   log pseudolikelihood = -1245.2302  
Iteration 3:   log pseudolikelihood = -1240.7779  
Iteration 4:   log pseudolikelihood = -1240.7082  
Iteration 5:   log pseudolikelihood = -1240.7081  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     489.43
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1240.7081               Pseudo R2         =     0.2200

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
        initFatalMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |    .296682   .2119772     1.40   0.162    -.1187857    .7121496
         modcrazy15a |  -.1877456   .1064591    -1.76   0.078    -.3964017    .0209104
      reallycrazy15b |   .8116826   .1555725     5.22   0.000     .5067661    1.116599
         modcrazy15b |   .0377468   .1164183     0.32   0.746    -.1904288    .2659224
recentMIDs_byleadera |   .1890566    .035701     5.30   0.000      .119084    .2590293
recentMIDs_byleaderb |   .0141358   .0445713     0.32   0.751    -.0732224     .101494
               cinca |   .5007817   .7983695     0.63   0.530    -1.063994    2.065557
               cincb |   .9855677   .6578497     1.50   0.134     -.303794    2.274929
            cincperc |  -.1675933   .2314338    -0.72   0.469    -.6211951    .2860086
                dema |   .0372972   .0790191     0.47   0.637    -.1175773    .1921718
                demb |   .0299914    .071785     0.42   0.676    -.1107046    .1706873
            jointdem |  -.5004657    .129943    -3.85   0.000    -.7551493   -.2457821
          landcontig |   .5273164   .0791617     6.66   0.000     .3721623    .6824704
            distance |  -.0828571   .0264299    -3.13   0.002    -.1346589   -.0310554
          dyadlength |   .5724816   .1154957     4.96   0.000     .3461141     .798849
        peaceyrs_fat |  -.0441731   .0064507    -6.85   0.000    -.0568162     -.03153
     peaceyrs_fat_sq |    .000636     .00014     4.54   0.000     .0003617    .0009103
    peaceyrs_fat_cub |  -2.50e-06   7.63e-07    -3.28   0.001    -4.00e-06   -1.01e-06
               _cons |  -2.671263   .2042954   -13.08   0.000    -3.071675   -2.270851
--------------------------------------------------------------------------------------
Note: 13 failures and 0 successes completely determined.
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A12: Different Sample and Dependent Variables (Initiation Model)") mtitles("No Political
> ly Relevant Restriction" "Only Dyads with a MID in Last 15 Years" "Forceful MID DV" "Fatal MID DV
> ")
(output written to appendix.rtf)

. eststo clear

. 
. * Table A13: Interaction
. eststo: probit initMID reallycrazy15a##reallycrazy15b modcrazy15a##modcrazy15b recentMIDs_byleade
> ra recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength pe
> aceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

note: 1.reallycrazy15a#1.reallycrazy15b identifies no observations in the sample
Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2457.6142  
Iteration 2:   log pseudolikelihood = -2291.3537  
Iteration 3:   log pseudolikelihood = -2284.6223  
Iteration 4:   log pseudolikelihood = -2284.5682  
Iteration 5:   log pseudolikelihood = -2284.5682  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(19)     =     867.24
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2284.5682               Pseudo R2         =     0.2486

                                              (Std. Err. adjusted for 1,554 clusters in dyadid)
-----------------------------------------------------------------------------------------------
                              |               Robust
                      initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------------+----------------------------------------------------------------
             1.reallycrazy15a |   .1623965   .2108914     0.77   0.441     -.250943     .575736
             1.reallycrazy15b |   .9094386    .140502     6.47   0.000     .6340596    1.184817
                              |
reallycrazy15a#reallycrazy15b |
                         1 1  |          0  (empty)
                              |
                1.modcrazy15a |   .0503528   .0755684     0.67   0.505    -.0977585    .1984642
                1.modcrazy15b |   .0921207   .0834397     1.10   0.270     -.071418    .2556595
                              |
      modcrazy15a#modcrazy15b |
                         1 1  |   .4399684   .2267754     1.94   0.052    -.0045031    .8844399
                              |
         recentMIDs_byleadera |   .2342675   .0306433     7.64   0.000     .1742077    .2943272
         recentMIDs_byleaderb |   .0511609   .0318739     1.61   0.108    -.0113107    .1136326
                        cinca |    1.76024   .7733198     2.28   0.023     .2445611    3.275919
                        cincb |    1.39023    .585834     2.37   0.018     .2420167    2.538444
                     cincperc |  -.0155919   .1697466    -0.09   0.927    -.3482891    .3171053
                         dema |   .1049238   .0608654     1.72   0.085    -.0143702    .2242178
                         demb |    .102565   .0616263     1.66   0.096    -.0182204    .2233503
                     jointdem |  -.4870646   .1067633    -4.56   0.000    -.6963168   -.2778123
                   landcontig |   .5362037   .0724537     7.40   0.000     .3941971    .6782104
                     distance |  -.1201646   .0242913    -4.95   0.000    -.1677747   -.0725545
                   dyadlength |   .6290882   .0773823     8.13   0.000     .4774217    .7807547
                     peaceyrs |  -.0423406   .0039728   -10.66   0.000    -.0501272    -.034554
                  peaceyrs_sq |   .0005364   .0000725     7.40   0.000     .0003943    .0006785
                 peaceyrs_cub |  -1.85e-06   3.41e-07    -5.44   0.000    -2.52e-06   -1.18e-06
                        _cons |  -2.633005   .1487611   -17.70   0.000    -2.924572   -2.341439
-----------------------------------------------------------------------------------------------
(est1 stored)

. margins, at(modcrazy15a=0 reallycrazy15a=0 modcrazy15b=0 reallycrazy15b=0 ) saving(file1, replace
> )

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           0
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0077139   .0005159    14.95   0.000     .0067027    .0087251
------------------------------------------------------------------------------

. margins, at(modcrazy15a=0 reallycrazy15a=0 modcrazy15b=1 reallycrazy15b=0 ) saving(file2, replace
> ) 

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           0
               modcrazy15b     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0094405   .0017251     5.47   0.000     .0060595    .0128216
------------------------------------------------------------------------------

. margins, at(modcrazy15a=1 reallycrazy15a=0 modcrazy15b=0 reallycrazy15b=0 ) saving(file3, replace
> )

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           1
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0086199   .0014017     6.15   0.000     .0058727    .0113671
------------------------------------------------------------------------------

. margins, at(modcrazy15a=1 reallycrazy15a=0 modcrazy15b=1 reallycrazy15b=0 ) saving(file4, replace
> )

Predictive margins                              Number of obs     =     62,384
Model VCE    : Robust

Expression   : Pr(initMID), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           1
               modcrazy15b     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .0254013   .0088993     2.85   0.004     .0079591    .0428435
------------------------------------------------------------------------------
(note: file file4.dta not found)

. combomarginsplot file1 file2 file3 file4, recast(bar)

  Variables that uniquely identify margins: _filenumber

. graph save Graph "Slight_Rep_Interaction_Det.gph", replace
(note: file Slight_Rep_Interaction_Det.gph not found)
(file Slight_Rep_Interaction_Det.gph saved)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A13: Interaction (Initiation Model)")
(output written to appendix.rtf)

. eststo clear 

. 
. 
. 
. ****************************** CRISIS BARGAINING ROBUSTNESS CHECKS ******************************
> *******
. 
. use "Crazy Leader MID Data", clear

. drop if tpopa<500 | tpopb<500
(19 observations deleted)

. 
. * Table A14: Compellence Regressions with Alternate Dummy Madness Measures and Dropping Outliers
. eststo: probit recip reallycrazy5a modcrazy5a reallycrazy5b modcrazy5b recentMIDs_byleadera recen
> tMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, cluster(c
> codea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -494.03677  
Iteration 2:   log pseudolikelihood = -493.94445  
Iteration 3:   log pseudolikelihood = -493.94445  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      65.74
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -493.94445               Pseudo R2         =     0.0479

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
       reallycrazy5a |   .6934412   .2188063     3.17   0.002     .2645888    1.122294
          modcrazy5a |  -.1661945   .1985818    -0.84   0.403    -.5554078    .2230187
       reallycrazy5b |   .6935443   .4015444     1.73   0.084    -.0934682    1.480557
          modcrazy5b |  -.4932098    .146783    -3.36   0.001    -.7808992   -.2055205
recentMIDs_byleadera |    -.02632   .1060266    -0.25   0.804    -.2341282    .1814883
recentMIDs_byleaderb |   .0622817   .0926765     0.67   0.502    -.1193609    .2439243
               cinca |  -.0340565   2.199604    -0.02   0.988    -4.345202    4.277089
               cincb |     -2.223   1.573578    -1.41   0.158    -5.307156    .8611559
            cincperc |   .4442897   .5420393     0.82   0.412    -.6180877    1.506667
                dema |  -.2176157   .2028337    -1.07   0.283    -.6151625    .1799311
                demb |  -.0099953    .155533    -0.06   0.949    -.3148343    .2948437
            jointdem |  -.1227939    .296459    -0.41   0.679     -.703843    .4582551
          landcontig |   .3195402   .1337787     2.39   0.017     .0573387    .5817417
            distance |   .0476958   .0453167     1.05   0.293    -.0411234    .1365149
          in1hostlev |  -.0381757   .1430055    -0.27   0.790    -.3184614      .24211
               _cons |  -.3554249   .5962227    -0.60   0.551       -1.524    .8131501
--------------------------------------------------------------------------------------
(est1 stored)

. eststo: probit recip reallycrazy10a modcrazy10a reallycrazy10b modcrazy10b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -498.75293  
Iteration 2:   log pseudolikelihood = -498.69063  
Iteration 3:   log pseudolikelihood = -498.69062  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      63.69
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.69062               Pseudo R2         =     0.0388

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy10a |   .7072233   .2219094     3.19   0.001     .2722889    1.142158
         modcrazy10a |  -.1689133   .2105844    -0.80   0.422    -.5816511    .2438246
      reallycrazy10b |  -.2711895   .2228365    -1.22   0.224     -.707941    .1655621
         modcrazy10b |  -.3695552   .1635327    -2.26   0.024    -.6900733   -.0490371
recentMIDs_byleadera |  -.0328963   .1051797    -0.31   0.754    -.2390448    .1732522
recentMIDs_byleaderb |   .0914686     .09682     0.94   0.345    -.0982952    .2812324
               cinca |  -.1247132   2.199823    -0.06   0.955    -4.436286     4.18686
               cincb |   -2.51412   1.595604    -1.58   0.115    -5.641447    .6132066
            cincperc |   .3156942   .5357775     0.59   0.556    -.7344105    1.365799
                dema |  -.2147627   .2011648    -1.07   0.286    -.6090385    .1795132
                demb |  -.0104586   .1565138    -0.07   0.947      -.31722    .2963028
            jointdem |  -.1407889   .2984447    -0.47   0.637    -.7257298     .444152
          landcontig |   .3319922   .1344165     2.47   0.014     .0685406    .5954438
            distance |   .0533695   .0437884     1.22   0.223    -.0324543    .1391932
          in1hostlev |  -.0419514   .1440676    -0.29   0.771    -.3243187    .2404159
               _cons |  -.2955147   .5972043    -0.49   0.621    -1.466014    .8749843
--------------------------------------------------------------------------------------
(est2 stored)

. eststo: probit recip reallycrazy20a modcrazy20a reallycrazy20b modcrazy20b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -498.39299  
Iteration 2:   log pseudolikelihood = -498.28104  
Iteration 3:   log pseudolikelihood = -498.28104  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      71.17
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.28104               Pseudo R2         =     0.0396

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy20a |   .2473494   .1830472     1.35   0.177    -.1114166    .6061154
         modcrazy20a |  -.1430027   .2173596    -0.66   0.511    -.5690196    .2830142
      reallycrazy20b |  -.6015936   .1956431    -3.07   0.002     -.985047   -.2181403
         modcrazy20b |  -.0720383   .1953677    -0.37   0.712     -.454952    .3108753
recentMIDs_byleadera |  -.0427592   .1058724    -0.40   0.686    -.2502653     .164747
recentMIDs_byleaderb |   .0925224   .0967776     0.96   0.339    -.0971583    .2822031
               cinca |  -.3976205    2.12263    -0.19   0.851    -4.557899    3.762658
               cincb |  -2.770405   1.615323    -1.72   0.086     -5.93638    .3955702
            cincperc |   .1635038   .5038693     0.32   0.746     -.824062    1.151069
                dema |  -.2024236   .2010978    -1.01   0.314     -.596568    .1917207
                demb |  -.0207872   .1562181    -0.13   0.894     -.326969    .2853946
            jointdem |  -.1624148   .3010152    -0.54   0.590    -.7523938    .4275642
          landcontig |   .2979563   .1368915     2.18   0.030     .0296539    .5662588
            distance |   .0418688   .0412359     1.02   0.310    -.0389522    .1226897
          in1hostlev |  -.0678272   .1487482    -0.46   0.648    -.3593682    .2237139
               _cons |  -.0770405   .6168441    -0.12   0.901    -1.286033    1.131952
--------------------------------------------------------------------------------------
(est3 stored)

. eststo: probit recip crazyscore_l1a crazyscore_l1b recentMIDs_byleadera recentMIDs_byleaderb cinc
> a cincb cincperc dema demb jointdem landcontig distance in1hostlev if crazyscore_l1a<=3.457385778
> 42712, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -514.02293  
Iteration 1:   log pseudolikelihood = -498.58613  
Iteration 2:   log pseudolikelihood = -498.55954  
Iteration 3:   log pseudolikelihood = -498.55954  

Probit regression                               Number of obs     =        753
                                                Wald chi2(13)     =      52.22
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.55954               Pseudo R2         =     0.0301

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_l1a |    .110495   .1209195     0.91   0.361    -.1265029    .3474929
      crazyscore_l1b |   .0462636   .1229134     0.38   0.707    -.1946422    .2871695
recentMIDs_byleadera |  -.0419114   .1013841    -0.41   0.679    -.2406205    .1567977
recentMIDs_byleaderb |   .0541435   .0944652     0.57   0.567     -.131005    .2392919
               cinca |  -.1850833   2.145369    -0.09   0.931    -4.389929    4.019762
               cincb |   -2.22331   1.517543    -1.47   0.143     -5.19764    .7510192
            cincperc |   .3160062    .530958     0.60   0.552    -.7246525    1.356665
                dema |  -.2464662   .2019188    -1.22   0.222    -.6422198    .1492873
                demb |   .0158833   .1615653     0.10   0.922    -.3007789    .3325455
            jointdem |  -.1407638   .3065997    -0.46   0.646    -.7416881    .4601605
          landcontig |   .4036331   .1308063     3.09   0.002     .1472575    .6600088
            distance |   .0432501   .0431352     1.00   0.316    -.0412934    .1277936
          in1hostlev |  -.0326319   .1509573    -0.22   0.829    -.3285027     .263239
               _cons |  -.4024326   .6086005    -0.66   0.508    -1.595268    .7904026
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A14: Alternate Indicator Cutoffs and Dropping Outliers (Recip Model)") mtitles("Top 5% I
> ndicator Cutoff" "Top 10% Indicator Cutoff" "Top 20% Indicator Cutoff" "Cont. Measure, Dropping T
> op 1%") 
(output written to appendix.rtf)

. eststo clear

. 
. 
. * Table A15: Address Potential Regional and Time Bias
. // Region fixed effects
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev i.regi
> ona i.regionb, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -490.25112  
Iteration 2:   log pseudolikelihood = -490.11956  
Iteration 3:   log pseudolikelihood = -490.11956  

Probit regression                               Number of obs     =        759
                                                Wald chi2(23)     =     176.11
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -490.11956               Pseudo R2         =     0.0553

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .2636166   .1322622     1.99   0.046     .0043875    .5228457
         modcrazy15a |  -.1396698   .1976113    -0.71   0.480    -.5269809    .2476413
      reallycrazy15b |  -.5457207   .2224142    -2.45   0.014    -.9816445   -.1097968
         modcrazy15b |  -.2416823   .1758304    -1.37   0.169    -.5863035    .1029388
recentMIDs_byleadera |  -.0476999    .096524    -0.49   0.621    -.2368834    .1414836
recentMIDs_byleaderb |   .1361157   .0992682     1.37   0.170    -.0584463    .3306777
               cinca |  -.0887053   1.930254    -0.05   0.963    -3.871934    3.694524
               cincb |  -2.884666   1.797743    -1.60   0.109    -6.408178    .6388464
            cincperc |  -.3628119   .7002671    -0.52   0.604     -1.73531    1.009686
                dema |  -.1520188   .2275571    -0.67   0.504    -.5980226     .293985
                demb |   .0230854   .1428382     0.16   0.872    -.2568723    .3030432
            jointdem |  -.2875811   .3050773    -0.94   0.346    -.8855217    .3103595
          landcontig |   .2646083   .1366709     1.94   0.053    -.0032619    .5324784
            distance |   .0229315   .0393303     0.58   0.560    -.0541545    .1000175
          in1hostlev |  -.0646647   .1351261    -0.48   0.632     -.329507    .2001776
                     |
             regiona |
                  2  |  -.2475585   .2926553    -0.85   0.398    -.8211524    .3260354
                  3  |   .3471473     .38408     0.90   0.366    -.4056358     1.09993
                  4  |    .413032   .3866205     1.07   0.285    -.3447302    1.170794
                  5  |   .0805973   .3843794     0.21   0.834    -.6727725    .8339671
                     |
             regionb |
                  2  |  -.3013724   .2459645    -1.23   0.220     -.783454    .1807092
                  3  |  -.5198104   .3381569    -1.54   0.124    -1.182586     .142965
                  4  |  -.4160185   .3540815    -1.17   0.240    -1.110005    .2779685
                  5  |  -.3075502   .3364201    -0.91   0.361    -.9669214     .351821
                     |
               _cons |   .3805321   .7004345     0.54   0.587    -.9922943    1.753358
--------------------------------------------------------------------------------------
(est1 stored)

. //Time fixed effects
. gen time=1 if year<1991
(760 missing values generated)

. replace time=2 if year>1990 & year<1995
(163 real changes made)

. replace time=3 if year>1994 & year<1999
(163 real changes made)

. replace time=4 if year>1998 & year<2003
(211 real changes made)

. replace time=5 if year>2002 & year<2007
(138 real changes made)

. replace time=6 if year>2006
(85 real changes made)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev i.time
> , cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -484.32331  
Iteration 2:   log pseudolikelihood = -484.16016  
Iteration 3:   log pseudolikelihood = -484.16015  

Probit regression                               Number of obs     =        759
                                                Wald chi2(20)     =     120.70
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -484.16015               Pseudo R2         =     0.0668

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .5799231   .2177761     2.66   0.008     .1530898    1.006756
         modcrazy15a |  -.0058498   .2039462    -0.03   0.977     -.405577    .3938774
      reallycrazy15b |  -.3958187   .2219772    -1.78   0.075    -.8308861    .0392487
         modcrazy15b |  -.0669754    .172124    -0.39   0.697    -.4043323    .2703815
recentMIDs_byleadera |  -.0561845   .0794845    -0.71   0.480    -.2119712    .0996023
recentMIDs_byleaderb |   .1082665   .0982659     1.10   0.271     -.084331     .300864
               cinca |   .1464975   1.809419     0.08   0.935    -3.399899    3.692894
               cincb |  -3.206917   1.646463    -1.95   0.051    -6.433925    .0200905
            cincperc |   .2347332   .5091946     0.46   0.645    -.7632698    1.232736
                dema |  -.1715809   .1960869    -0.88   0.382    -.5559042    .2127424
                demb |   .0130502   .1684757     0.08   0.938    -.3171561    .3432566
            jointdem |  -.1485782   .3094206    -0.48   0.631    -.7550313     .457875
          landcontig |   .3585434   .1415612     2.53   0.011     .0810885    .6359983
            distance |   .0350119   .0395473     0.89   0.376    -.0424995    .1125232
          in1hostlev |  -.0270235   .1289737    -0.21   0.834    -.2798074    .2257604
                     |
                time |
                  2  |  -.4283283   .2131761    -2.01   0.045    -.8461458   -.0105108
                  3  |  -.1712137   .2223735    -0.77   0.441    -.6070577    .2646303
                  4  |  -.8087748   .2015393    -4.01   0.000    -1.203785    -.413765
                  5  |  -.4587492    .190431    -2.41   0.016    -.8319871   -.0855114
                  6  |  -.3638805    .190479    -1.91   0.056    -.7372125    .0094515
                     |
               _cons |   .0292561   .6493763     0.05   0.964    -1.243498     1.30201
--------------------------------------------------------------------------------------
(est2 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A15: Address Regional and Time Bias (Recip Model)")  mtitles("Region Fixed Effects" "Tim
> e Fixed Effects")
(output written to appendix.rtf)

. eststo clear

. 
. * Table A16: Address Pro-Western Bias and Strategic Use of Madness Adjectives
. // Control for affinity with the US
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b affinity_us_a affinity
> _us_b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landconti
> g distance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -494.88597  
Iteration 1:   log pseudolikelihood =  -472.3251  
Iteration 2:   log pseudolikelihood = -472.23441  
Iteration 3:   log pseudolikelihood = -472.23439  

Probit regression                               Number of obs     =        723
                                                Wald chi2(17)     =      81.74
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -472.23439               Pseudo R2         =     0.0458

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .3961187   .1388926     2.85   0.004     .1238943    .6683431
         modcrazy15a |  -.0140291     .19857    -0.07   0.944     -.403219    .3751609
      reallycrazy15b |  -.4464499   .2003631    -2.23   0.026    -.8391544   -.0537454
         modcrazy15b |  -.2617164   .1760324    -1.49   0.137    -.6067335    .0833007
       affinity_us_a |  -.4107309   .2385248    -1.72   0.085     -.878231    .0567691
       affinity_us_b |   .0146236   .2019206     0.07   0.942    -.3811334    .4103806
recentMIDs_byleadera |  -.0178315   .1001076    -0.18   0.859    -.2140387    .1783757
recentMIDs_byleaderb |   .0946413   .0982607     0.96   0.335    -.0979461    .2872287
               cinca |  -.0996112   2.252077    -0.04   0.965      -4.5136    4.314378
               cincb |  -1.306841   1.839747    -0.71   0.477    -4.912678    2.298996
            cincperc |  -.1326473   .5936973    -0.22   0.823    -1.296273    1.030978
                dema |  -.1302643   .2157928    -0.60   0.546    -.5532104    .2926817
                demb |  -.0583556   .1534556    -0.38   0.704     -.359123    .2424118
            jointdem |  -.0745761   .3257605    -0.23   0.819    -.7130549    .5639026
          landcontig |    .307016   .1451056     2.12   0.034     .0226142    .5914178
            distance |   .0484331   .0462757     1.05   0.295    -.0422655    .1391318
          in1hostlev |  -.0451649   .1494348    -0.30   0.762    -.3380517    .2477219
               _cons |  -.1913035   .5362552    -0.36   0.721    -1.242344    .8597375
--------------------------------------------------------------------------------------
(est1 stored)

. // Use only non-US sources
. eststo: probit recip reallycrazy15_nousa modcrazy15_nousa reallycrazy15_nousb modcrazy15_nousb re
> centMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distan
> ce in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -500.16672  
Iteration 2:   log pseudolikelihood = -500.11839  
Iteration 3:   log pseudolikelihood = -500.11839  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      55.16
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -500.11839               Pseudo R2         =     0.0360

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
 reallycrazy15_nousa |   .4402263   .2556994     1.72   0.085    -.0609354     .941388
    modcrazy15_nousa |   -.133194   .2173065    -0.61   0.540    -.5591069    .2927188
 reallycrazy15_nousb |  -.2210146   .2310574    -0.96   0.339    -.6738788    .2318495
    modcrazy15_nousb |  -.3771502   .1636777    -2.30   0.021    -.6979526   -.0563478
recentMIDs_byleadera |  -.0367655   .1063532    -0.35   0.730    -.2452139    .1716829
recentMIDs_byleaderb |   .0825958   .0960838     0.86   0.390    -.1057251    .2709166
               cinca |  -.1456219   2.179307    -0.07   0.947    -4.416985    4.125741
               cincb |  -2.388458   1.585668    -1.51   0.132     -5.49631    .7193944
            cincperc |   .3182789   .5190946     0.61   0.540    -.6991278    1.335686
                dema |  -.2153214   .1995679    -1.08   0.281    -.6064672    .1758245
                demb |  -.0117821   .1591201    -0.07   0.941    -.3236517    .3000876
            jointdem |  -.1652069   .3026668    -0.55   0.585    -.7584229    .4280092
          landcontig |   .3341338   .1337492     2.50   0.012     .0719902    .5962774
            distance |   .0500484   .0447062     1.12   0.263    -.0375742     .137671
          in1hostlev |  -.0565104   .1464294    -0.39   0.700    -.3435068    .2304859
               _cons |  -.2449239   .6023198    -0.41   0.684    -1.425449    .9356012
--------------------------------------------------------------------------------------
(est2 stored)

. // Drop English-speaking Western countries 
. preserve

. drop if ccodea<21 | ccodea==200 | ccodea==205 | ccodea==900 | ccodea==920 | ccodeb<21 | ccodeb==2
> 00 | ccodeb==205 | ccodeb==900 | ccodeb==920
(130 observations deleted)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -446.67437  
Iteration 1:   log pseudolikelihood = -425.09145  
Iteration 2:   log pseudolikelihood = -424.99587  
Iteration 3:   log pseudolikelihood = -424.99586  

Probit regression                               Number of obs     =        651
                                                Wald chi2(15)     =      95.98
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -424.99586               Pseudo R2         =     0.0485

                                       (Std. Err. adjusted for 109 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4962068   .1449241     3.42   0.001     .2121608    .7802528
         modcrazy15a |  -.2290437   .2167361    -1.06   0.291    -.6538386    .1957512
      reallycrazy15b |   -.616782   .2745275    -2.25   0.025    -1.154846   -.0787179
         modcrazy15b |  -.5865402   .2869128    -2.04   0.041    -1.148879   -.0242015
recentMIDs_byleadera |  -.0656232    .103275    -0.64   0.525    -.2680385    .1367921
recentMIDs_byleaderb |   .0802156   .1203149     0.67   0.505    -.1555974    .3160285
               cinca |   -.373053   1.981828    -0.19   0.851    -4.257364    3.511258
               cincb |  -2.872963   1.706501    -1.68   0.092    -6.217644    .4717176
            cincperc |   .9326603   1.005118     0.93   0.353    -1.037335    2.902656
                dema |  -.2535822   .2230756    -1.14   0.256    -.6908024    .1836381
                demb |  -.0577001   .1455123    -0.40   0.692     -.342899    .2274988
            jointdem |   .0395097   .3059391     0.13   0.897    -.5601199    .6391392
          landcontig |   .2683929   .1506171     1.78   0.075    -.0268112     .563597
            distance |  -.0170922   .0710352    -0.24   0.810    -.1563186    .1221341
          in1hostlev |  -.0361079   .1504043    -0.24   0.810     -.330895    .2586792
               _cons |   -.468367   .5824545    -0.80   0.421    -1.609957    .6732228
--------------------------------------------------------------------------------------
(est3 stored)

. restore

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A16: Address Pro-Western Bias and Strategic Use of Madness Adjectives (Recip Model)")  m
> titles("Control for US Affinity" "Only Non-US Sources" "Drop English-Speaking Western Countries")
(output written to appendix.rtf)

. eststo clear 

. 
. 
. * Table A17: Control for and Match on Other Characteristics Associated with Perceived Madness and
>  Control for Reputation
. // Control for years in office
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b yrs_in_ofc_l1a recentM
> IDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in
> 1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -498.86429  
Iteration 2:   log pseudolikelihood = -498.78284  
Iteration 3:   log pseudolikelihood = -498.78283  

Probit regression                               Number of obs     =        759
                                                Wald chi2(16)     =      85.29
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.78283               Pseudo R2         =     0.0386

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4403704   .1557462     2.83   0.005     .1351134    .7456274
         modcrazy15a |  -.1607566   .2158965    -0.74   0.457    -.5839061    .2623928
      reallycrazy15b |    -.54924   .1998243    -2.75   0.006    -.9408884   -.1575915
         modcrazy15b |  -.2073452   .1753683    -1.18   0.237    -.5510608    .1363704
      yrs_in_ofc_l1a |   .0010986   .0108699     0.10   0.919     -.020206    .0224032
recentMIDs_byleadera |  -.0380259   .1066787    -0.36   0.722    -.2471124    .1710605
recentMIDs_byleaderb |   .0981711   .0980619     1.00   0.317    -.0940268    .2903689
               cinca |   -.224124    2.15912    -0.10   0.917    -4.455921    4.007673
               cincb |  -2.660366   1.581274    -1.68   0.092    -5.759607    .4388747
            cincperc |   .2421783   .5205611     0.47   0.642    -.7781027    1.262459
                dema |   -.191686   .2031264    -0.94   0.345    -.5898064    .2064344
                demb |  -.0144372    .157893    -0.09   0.927    -.3239018    .2950274
            jointdem |  -.1775442   .3010022    -0.59   0.555    -.7674976    .4124093
          landcontig |   .3131934    .134698     2.33   0.020     .0491903    .5771966
            distance |   .0464036   .0428475     1.08   0.279     -.037576    .1303831
          in1hostlev |  -.0580122   .1479023    -0.39   0.695    -.3478954     .231871
               _cons |  -.1877201   .6034809    -0.31   0.756    -1.370521    .9950806
--------------------------------------------------------------------------------------
(est1 stored)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev if yrs
> _in_ofc_l1a>4, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -308.54403  
Iteration 1:   log pseudolikelihood = -288.60099  
Iteration 2:   log pseudolikelihood = -288.49847  
Iteration 3:   log pseudolikelihood = -288.49843  
Iteration 4:   log pseudolikelihood = -288.49843  

Probit regression                               Number of obs     =        449
                                                Wald chi2(15)     =     114.88
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -288.49843               Pseudo R2         =     0.0650

                                        (Std. Err. adjusted for 96 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4796263   .1548499     3.10   0.002      .176126    .7831266
         modcrazy15a |  -.5039574   .2811212    -1.79   0.073    -1.054945      .04703
      reallycrazy15b |  -.8659126   .4458163    -1.94   0.052    -1.739696    .0078714
         modcrazy15b |   .0231961   .2140317     0.11   0.914    -.3962983    .4426905
recentMIDs_byleadera |   .0926034   .1405055     0.66   0.510    -.1827824    .3679892
recentMIDs_byleaderb |   .1319015   .1432602     0.92   0.357    -.1488834    .4126864
               cinca |  -3.679212   1.373474    -2.68   0.007    -6.371171   -.9872527
               cincb |  -2.102879   1.939118    -1.08   0.278     -5.90348    1.697722
            cincperc |   .8944777   .6070647     1.47   0.141    -.2953473    2.084303
                dema |   .0459738   .3022481     0.15   0.879    -.5464215    .6383691
                demb |  -.1091506   .1731856    -0.63   0.529     -.448588    .2302869
            jointdem |  -.4641796   .4476512    -1.04   0.300     -1.34156    .4132007
          landcontig |   .2366292   .1853345     1.28   0.202    -.1266197    .5998781
            distance |   .0460923   .0514409     0.90   0.370    -.0547301    .1469147
          in1hostlev |  -.0008453   .1945881    -0.00   0.997     -.382231    .3805404
               _cons |  -.7009075   .7342125    -0.95   0.340    -2.139938    .7381225
--------------------------------------------------------------------------------------
(est2 stored)

. // Matching
. preserve

. drop if reallycrazy15a==. | modcrazy15a==. | yrs_in_ofc_l1a==. | rebel_l1a==. | personalist_l1a==
> .
(342 observations deleted)

. gen anycrazya=(reallycrazy15a==1 | modcrazy15a==1)

. cem  westa (.5) personalist_l1a (.5) recentMIDs_statea (2.5) rebel_l1a (.5) yrs_in_ofc_l1a (4.5 8
> .5), tr(anycrazya)

Matching Summary:
-----------------
Number of strata: 32
Number of matched strata: 13

             0    1
      All  504   66
  Matched  308   66
Unmatched  196    0


Multivariate L1 distance: .79244529

Univariate imbalance:

                        L1     mean      min      25%      50%      75%      max
            westa  1.4e-16  2.2e-16        0        0        0        0        0
  personalist_l1a  7.5e-16  5.0e-16        0        0        0        0        0
recentMIDs_statea    .5028  -.09961        0       .4        0      -.6        0
        rebel_l1a  7.2e-16  2.2e-16        0        0        0        0        0
   yrs_in_ofc_l1a   .30178   .73365        0        0        2        1       -3

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev [iweig
> ht=cem_weights], cluster(ccodea)

Iteration 0:   log pseudolikelihood = -214.25219  
Iteration 1:   log pseudolikelihood = -162.94464  
Iteration 2:   log pseudolikelihood = -160.92252  
Iteration 3:   log pseudolikelihood = -160.91627  
Iteration 4:   log pseudolikelihood = -160.91627  

Probit regression                               Number of obs     =        347
                                                Wald chi2(15)     =     550.09
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -160.91627               Pseudo R2         =     0.2489

                                        (Std. Err. adjusted for 76 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .7143344   .3944416     1.81   0.070     -.058757    1.487426
         modcrazy15a |    .317487   .3293285     0.96   0.335     -.327985     .962959
      reallycrazy15b |  -.4479466   .5202546    -0.86   0.389    -1.467627    .5717336
         modcrazy15b |   .0831234   .2898867     0.29   0.774    -.4850441    .6512908
recentMIDs_byleadera |  -.6432386   .1482731    -4.34   0.000    -.9338485   -.3526286
recentMIDs_byleaderb |   .1849925   .1923505     0.96   0.336    -.1920075    .5619924
               cinca |   .5291831   2.840197     0.19   0.852    -5.037501    6.095867
               cincb |  -1.975634   4.142144    -0.48   0.633    -10.09409     6.14282
            cincperc |  -1.481042   1.018219    -1.45   0.146    -3.476715    .5146314
                dema |  -1.010255   .3777853    -2.67   0.007    -1.750701   -.2698095
                demb |  -.0388723   .1888102    -0.21   0.837    -.4089334    .3311889
            jointdem |  -.1322545    .677781    -0.20   0.845    -1.460681    1.196172
          landcontig |  -.1122897   .1666456    -0.67   0.500    -.4389091    .2143296
            distance |   .0202877   .0481913     0.42   0.674    -.0741656    .1147409
          in1hostlev |   -.931414   .3128169    -2.98   0.003    -1.544524   -.3183041
               _cons |   4.114322   1.098058     3.75   0.000     1.962168    6.266475
--------------------------------------------------------------------------------------
(est3 stored)

. restore

. // Drop strategic blunders
. gen MPtargetMID=((ccodeb==2 | ccodeb==200 | ccodeb==220 | ccodeb==365 | ccodeb==710) & origb==1)

. gsort dispn -MPtargetMID

. by dispn: replace MPtargetMID=1 if MPtargetMID[_n-1]==1
(49 real changes made)

. replace MPtargetMID=0 if MPtargetMID==.
(0 real changes made)

. gen MPinitMID=((ccodea==2 | ccodea==200 | ccodea==220 | ccodea==365 | ccodea==710) & origa==1)

. gsort dispn -MPinitMID

. by dispn: replace MPinitMID=1 if MPinitMID[_n-1]==1
(87 real changes made)

. replace MPinitMID=0 if MPinitMID==.
(0 real changes made)

. gen blunder=(MPtargetMID==1 & MPinitMID==0)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev if blu
> nder==0, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -484.93306  
Iteration 1:   log pseudolikelihood = -466.47486  
Iteration 2:   log pseudolikelihood = -466.39136  
Iteration 3:   log pseudolikelihood = -466.39135  

Probit regression                               Number of obs     =        707
                                                Wald chi2(15)     =      99.98
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -466.39135               Pseudo R2         =     0.0382

                                       (Std. Err. adjusted for 111 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4392208   .1594126     2.76   0.006     .1267777    .7516638
         modcrazy15a |  -.0648448   .2199966    -0.29   0.768    -.4960302    .3663405
      reallycrazy15b |  -.6184443   .1989409    -3.11   0.002    -1.008361   -.2285273
         modcrazy15b |  -.1831804   .1874471    -0.98   0.328      -.55057    .1842091
recentMIDs_byleadera |  -.0533622   .1099983    -0.49   0.628     -.268955    .1622305
recentMIDs_byleaderb |   .1244549   .1048332     1.19   0.235    -.0810144    .3299243
               cinca |  -.5156571   2.126747    -0.24   0.808    -4.684004    3.652689
               cincb |  -.2187717   2.846825    -0.08   0.939    -5.798446    5.360902
            cincperc |  -.0202255   .5953905    -0.03   0.973    -1.187169    1.146718
                dema |  -.1215486   .2095331    -0.58   0.562    -.5322259    .2891288
                demb |  -.0497117   .1477349    -0.34   0.736    -.3392668    .2398435
            jointdem |  -.1696299   .3047838    -0.56   0.578    -.7669952    .4277353
          landcontig |   .3468305   .1539213     2.25   0.024     .0451502    .6485108
            distance |   .0134539    .050095     0.27   0.788    -.0847305    .1116383
          in1hostlev |  -.0929748   .1528111    -0.61   0.543    -.3924792    .2065295
               _cons |   .0581182   .5754104     0.10   0.920    -1.069666    1.185902
--------------------------------------------------------------------------------------
(est4 stored)

. //Control for reputation
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recent_bluffsa recent_
> bluffsb recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcon
> tig distance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -494.41386  
Iteration 2:   log pseudolikelihood = -494.28509  
Iteration 3:   log pseudolikelihood = -494.28509  

Probit regression                               Number of obs     =        759
                                                Wald chi2(17)     =     123.84
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -494.28509               Pseudo R2         =     0.0473

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .2960843   .1464978     2.02   0.043     .0089538    .5832148
         modcrazy15a |  -.1420222   .1891118    -0.75   0.453    -.5126745    .2286302
      reallycrazy15b |  -.6042318   .2002583    -3.02   0.003    -.9967309   -.2117326
         modcrazy15b |  -.1865892   .1750311    -1.07   0.286    -.5296439    .1564655
      recent_bluffsa |  -.5042179   .2960452    -1.70   0.089    -1.084456      .07602
      recent_bluffsb |  -.3126471   .1830697    -1.71   0.088    -.6714571    .0461629
recentMIDs_byleadera |   .1467088   .1755609     0.84   0.403    -.1973841    .4908018
recentMIDs_byleaderb |   .2345735    .106576     2.20   0.028     .0256884    .4434586
               cinca |   .8795789   1.960901     0.45   0.654    -2.963716    4.722874
               cincb |  -1.841083   1.550646    -1.19   0.235    -4.880293    1.198128
            cincperc |   .2265452    .508264     0.45   0.656    -.7696339    1.222724
                dema |  -.1582048   .1905852    -0.83   0.406    -.5317449    .2153354
                demb |   .0153378   .1514318     0.10   0.919     -.281463    .3121386
            jointdem |  -.1714249   .2957516    -0.58   0.562    -.7510873    .4082375
          landcontig |   .3059252   .1342094     2.28   0.023     .0428796    .5689708
            distance |   .0235728   .0417382     0.56   0.572    -.0582326    .1053783
          in1hostlev |  -.0517037   .1330691    -0.39   0.698    -.3125144    .2091069
               _cons |  -.2207055     .56979    -0.39   0.699    -1.337473    .8960625
--------------------------------------------------------------------------------------
(est5 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A17: Address Potentially Confounding Leader and Country Characteristics (Recip Model)") 
> mtitles("Control for Years in Office" "Drop Leaders in Office <5 Years" "Matched Sample" "Drop St
> rategic Blunders" "Control for Reputation")
(output written to appendix.rtf)

. eststo clear

. 
. 
. * Table A18: Adjustments to Madness Measure and Comparison with Tough Score
. //Compare with tough score
. eststo: probit recip reallycrazy15a modcrazy15a reallytough15a modtough15a reallycrazy15b modcraz
> y15b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig
>  distance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -497.44182  
Iteration 2:   log pseudolikelihood = -497.33279  
Iteration 3:   log pseudolikelihood = -497.33279  

Probit regression                               Number of obs     =        759
                                                Wald chi2(17)     =      95.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -497.33279               Pseudo R2         =     0.0414

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4023199   .1598479     2.52   0.012     .0890237    .7156161
         modcrazy15a |  -.2438291   .2202878    -1.11   0.268    -.6755852     .187927
      reallytough15a |   .5685508   .3296265     1.72   0.085    -.0775052    1.214607
         modtough15a |   .0417003   .2485267     0.17   0.867    -.4454029    .5288036
      reallycrazy15b |  -.5718987   .2014755    -2.84   0.005    -.9667834    -.177014
         modcrazy15b |  -.2081207   .1860956    -1.12   0.263    -.5728614      .15662
recentMIDs_byleadera |  -.0460627     .10673    -0.43   0.666    -.2552497    .1631243
recentMIDs_byleaderb |   .1082597   .0984448     1.10   0.271    -.0846885    .3012079
               cinca |  -.2472224   2.174402    -0.11   0.909    -4.508972    4.014527
               cincb |  -2.851298   1.561613    -1.83   0.068    -5.912003    .2094061
            cincperc |   .2353234   .5155256     0.46   0.648    -.7750881    1.245735
                dema |  -.2322899    .204088    -1.14   0.255    -.6322951    .1677153
                demb |  -.0112008   .1573598    -0.07   0.943    -.3196202    .2972187
            jointdem |  -.1516994   .2993364    -0.51   0.612     -.738388    .4349893
          landcontig |   .3137389   .1357509     2.31   0.021      .047672    .5798058
            distance |   .0516829   .0481151     1.07   0.283    -.0426209    .1459867
          in1hostlev |  -.0642278   .1478252    -0.43   0.664    -.3539599    .2255042
               _cons |  -.1577808   .6155283    -0.26   0.798    -1.364194    1.048632
--------------------------------------------------------------------------------------
(est1 stored)

. // Use only words used in foreign policy context.
. eststo: probit recip reallycrazy15_fpa modcrazy15_fpa reallycrazy15_fpb modcrazy15_fpb recentMIDs
> _byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1ho
> stlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood =  -499.8498  
Iteration 2:   log pseudolikelihood = -499.80311  
Iteration 3:   log pseudolikelihood =  -499.8031  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      71.36
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -499.8031               Pseudo R2         =     0.0366

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
   reallycrazy15_fpa |   .7217964   .2249061     3.21   0.001     .2809886    1.162604
      modcrazy15_fpa |  -.1627013   .2410589    -0.67   0.500    -.6351681    .3097655
   reallycrazy15_fpb |  -.3305833   .2205866    -1.50   0.134     -.762925    .1017584
      modcrazy15_fpb |  -.2362073   .1765551    -1.34   0.181    -.5822489    .1098343
recentMIDs_byleadera |  -.0316871   .1072547    -0.30   0.768    -.2419024    .1785283
recentMIDs_byleaderb |   .0914583   .0972066     0.94   0.347    -.0990632    .2819797
               cinca |  -.1378552   2.184021    -0.06   0.950    -4.418458    4.142748
               cincb |  -2.553974   1.606341    -1.59   0.112    -5.702344    .5943965
            cincperc |   .2784992   .5334618     0.52   0.602    -.7670667    1.324065
                dema |  -.2111832   .2006542    -1.05   0.293    -.6044582    .1820917
                demb |   -.016007   .1560319    -0.10   0.918    -.3218239    .2898098
            jointdem |   -.148715   .3002971    -0.50   0.620    -.7372866    .4398566
          landcontig |   .3414457   .1336464     2.55   0.011     .0795035    .6033878
            distance |   .0475292   .0421206     1.13   0.259    -.0350257     .130084
          in1hostlev |  -.0424507   .1449215    -0.29   0.770    -.3264916    .2415903
               _cons |    -.28547    .598398    -0.48   0.633    -1.458309    .8873685
--------------------------------------------------------------------------------------
(est2 stored)

. // Averaging over different time periods
. eststo: probit recip reallycrazy15_avg5a modcrazy15_avg5a reallycrazy15_avg5b modcrazy15_avg5b re
> centMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distan
> ce in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -495.42847  
Iteration 2:   log pseudolikelihood = -495.32747  
Iteration 3:   log pseudolikelihood = -495.32747  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      54.00
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -495.32747               Pseudo R2         =     0.0453

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
 reallycrazy15_avg5a |   .0749769   .1739149     0.43   0.666      -.26589    .4158439
    modcrazy15_avg5a |  -.2283238   .1879834    -1.21   0.225    -.5967646     .140117
 reallycrazy15_avg5b |   -.295171   .1892856    -1.56   0.119    -.6661639    .0758219
    modcrazy15_avg5b |  -.5584862   .1372164    -4.07   0.000    -.8274254    -.289547
recentMIDs_byleadera |  -.0157991   .1023778    -0.15   0.877    -.2164559    .1848577
recentMIDs_byleaderb |   .1289332   .0986758     1.31   0.191    -.0644678    .3223343
               cinca |  -.0398879   2.385581    -0.02   0.987    -4.715541    4.635765
               cincb |  -2.727983   1.589829    -1.72   0.086    -5.843991    .3880253
            cincperc |   .3343401   .5575895     0.60   0.549    -.7585151    1.427195
                dema |  -.1796216   .2064104    -0.87   0.384    -.5841785    .2249353
                demb |  -.0105778   .1604627    -0.07   0.947    -.3250789    .3039232
            jointdem |  -.1910705   .2899508    -0.66   0.510    -.7593636    .3772226
          landcontig |   .3265223   .1433451     2.28   0.023     .0455711    .6074734
            distance |   .0578948    .044398     1.30   0.192    -.0291236    .1449132
          in1hostlev |  -.0598551   .1462294    -0.41   0.682    -.3464595    .2267492
               _cons |   -.218642   .6225887    -0.35   0.725    -1.438893    1.001609
--------------------------------------------------------------------------------------
(est3 stored)

. eststo: probit recip reallycrazy15_avg10a modcrazy15_avg10a reallycrazy15_avg10b modcrazy15_avg10
> b recentMIDs_byleadera recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig di
> stance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -500.57662  
Iteration 2:   log pseudolikelihood = -500.53175  
Iteration 3:   log pseudolikelihood = -500.53175  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      46.06
                                                Prob > chi2       =     0.0001
Log pseudolikelihood = -500.53175               Pseudo R2         =     0.0352

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
reallycrazy15_avg10a |  -.0596596   .1705049    -0.35   0.726    -.3938431     .274524
   modcrazy15_avg10a |  -.2466004   .1815458    -1.36   0.174    -.6024236    .1092227
reallycrazy15_avg10b |  -.3240496   .1897863    -1.71   0.088    -.6960239    .0479247
   modcrazy15_avg10b |  -.1064012   .1349268    -0.79   0.430    -.3708529    .1580506
recentMIDs_byleadera |  -.0071868   .1000433    -0.07   0.943    -.2032681    .1888946
recentMIDs_byleaderb |   .0938852   .0931649     1.01   0.314    -.0887148    .2764851
               cinca |  -.4724928   2.302175    -0.21   0.837    -4.984672    4.039686
               cincb |  -2.613988   1.587985    -1.65   0.100    -5.726381     .498405
            cincperc |   .1510573   .5390423     0.28   0.779    -.9054462    1.207561
                dema |  -.2257126   .2044866    -1.10   0.270    -.6264989    .1750737
                demb |  -.0127459   .1520292    -0.08   0.933    -.3107176    .2852258
            jointdem |  -.1857243   .2932316    -0.63   0.526    -.7604477     .388999
          landcontig |   .3240313   .1447623     2.24   0.025     .0403023    .6077603
            distance |   .0470227   .0434639     1.08   0.279    -.0381649    .1322103
          in1hostlev |  -.0545879    .145901    -0.37   0.708    -.3405485    .2313728
               _cons |  -.1256537   .6365132    -0.20   0.844    -1.373197    1.121889
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A18: Adjustments to the Madness Measure (Recip Model)")  mtitles("Compare to Tough Score
> " "Drop Words Used outside FP Context" "5-Year Average" "10-Year Average")
(output written to appendix.rtf)

. eststo clear

. 
. 
. * Table A19: Drop Some MIDs
. // Drop MIDs that began with use of force
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev if in1
> hostlev<4, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -316.44609  
Iteration 1:   log pseudolikelihood = -299.75602  
Iteration 2:   log pseudolikelihood = -299.67041  
Iteration 3:   log pseudolikelihood = -299.67039  

Probit regression                               Number of obs     =        468
                                                Wald chi2(15)     =     108.63
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -299.67039               Pseudo R2         =     0.0530

                                       (Std. Err. adjusted for 103 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .3710589    .167056     2.22   0.026     .0436351    .6984827
         modcrazy15a |  -.3150796   .2478054    -1.27   0.204    -.8007692      .17061
      reallycrazy15b |  -.4962346   .2068274    -2.40   0.016    -.9016089   -.0908604
         modcrazy15b |  -.1785726   .2207706    -0.81   0.419     -.611275    .2541298
recentMIDs_byleadera |   .0081603   .1084184     0.08   0.940    -.2043358    .2206564
recentMIDs_byleaderb |   .2311604   .1315559     1.76   0.079    -.0266844    .4890051
               cinca |  -.1844399   1.704629    -0.11   0.914    -3.525452    3.156572
               cincb |  -4.761491   2.549999    -1.87   0.062    -9.759398    .2364158
            cincperc |  -.0798487   .6230314    -0.13   0.898    -1.300968     1.14127
                dema |  -.0411517   .2333363    -0.18   0.860    -.4984825     .416179
                demb |   .1008424   .1786954     0.56   0.573    -.2493941    .4510788
            jointdem |  -.2454323   .3356571    -0.73   0.465    -.9033083    .4124436
          landcontig |   .3067935   .1869081     1.64   0.101    -.0595395    .6731266
            distance |   .0623735   .0388459     1.61   0.108    -.0137631    .1385101
          in1hostlev |  -.5622523   .3657864    -1.54   0.124     -1.27918    .1546759
               _cons |   1.185079   1.125446     1.05   0.292    -1.020755    3.390913
--------------------------------------------------------------------------------------
(est1 stored)

. // Drop non-revisionist MIDs
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev if non
> rev==0, cluster(ccodea)

Iteration 0:   log pseudolikelihood =  -331.4743  
Iteration 1:   log pseudolikelihood = -300.13369  
Iteration 2:   log pseudolikelihood = -299.86941  
Iteration 3:   log pseudolikelihood = -299.86912  
Iteration 4:   log pseudolikelihood = -299.86912  

Probit regression                               Number of obs     =        491
                                                Wald chi2(15)     =      70.93
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -299.86912               Pseudo R2         =     0.0953

                                       (Std. Err. adjusted for 101 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   -.367286   .4299912    -0.85   0.393    -1.210053    .4754812
         modcrazy15a |   .0443899   .1986592     0.22   0.823     -.344975    .4337549
      reallycrazy15b |  -.7594918   .2493589    -3.05   0.002    -1.248226   -.2707574
         modcrazy15b |   -.411111   .2649818    -1.55   0.121    -.9304658    .1082438
recentMIDs_byleadera |  -.1843486   .0770131    -2.39   0.017    -.3352915   -.0334056
recentMIDs_byleaderb |   .0204425    .131077     0.16   0.876    -.2364637    .2773487
               cinca |   .6710732   1.654045     0.41   0.685    -2.570795    3.912941
               cincb |  -2.483444   2.439024    -1.02   0.309    -7.263844    2.296956
            cincperc |  -1.018713   .4958278    -2.05   0.040    -1.990517   -.0469081
                dema |  -.1108113    .204986    -0.54   0.589    -.5125765    .2909539
                demb |  -.1112049   .2213809    -0.50   0.615    -.5451035    .3226937
            jointdem |  -.1686528   .4196242    -0.40   0.688    -.9911011    .6537956
          landcontig |     .44041   .1619505     2.72   0.007     .1229929    .7578271
            distance |  -.0660791   .0509159    -1.30   0.194    -.1658723    .0337142
          in1hostlev |   .1797271   .1262208     1.42   0.154    -.0676611    .4271154
               _cons |  -.2211219   .5523602    -0.40   0.689    -1.303728    .8614842
--------------------------------------------------------------------------------------
(est2 stored)

. // Retain only one originator observation per ccodeb in each dispute - because ccodeb holds the r
> ecip decision.
. preserve

. set seed 92478533

. gen randomorder=runiform()

. gsort -origa +randomorder

. duplicates drop dispnum3 ccodeb, force

Duplicates in terms of dispnum3 ccodeb

(125 observations deleted)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -442.19662  
Iteration 1:   log pseudolikelihood = -428.20821  
Iteration 2:   log pseudolikelihood = -428.17122  
Iteration 3:   log pseudolikelihood = -428.17122  

Probit regression                               Number of obs     =        643
                                                Wald chi2(15)     =      67.36
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -428.17122               Pseudo R2         =     0.0317

                                       (Std. Err. adjusted for 102 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4332065   .1562148     2.77   0.006     .1270311    .7393818
         modcrazy15a |  -.2860203   .2589238    -1.10   0.269    -.7935016    .2214611
      reallycrazy15b |  -.2235913   .1952472    -1.15   0.252    -.6062687    .1590862
         modcrazy15b |  -.1556864   .2201574    -0.71   0.479    -.5871871    .2758142
recentMIDs_byleadera |  -.0281335   .1160621    -0.24   0.808    -.2556109     .199344
recentMIDs_byleaderb |   .0296296   .0929315     0.32   0.750    -.1525128     .211772
               cinca |   -.276771   2.301317    -0.12   0.904    -4.787269    4.233727
               cincb |  -2.616316   1.837571    -1.42   0.155    -6.217889    .9852576
            cincperc |   .2631957   .5971352     0.44   0.659    -.9071678    1.433559
                dema |   -.149598    .237941    -0.63   0.530    -.6159539    .3167578
                demb |  -.0040604   .1733871    -0.02   0.981    -.3438929    .3357721
            jointdem |  -.1534342   .3334677    -0.46   0.645    -.8070189    .5001506
          landcontig |   .3777591   .1826842     2.07   0.039     .0197045    .7358136
            distance |   .0704518   .0459064     1.53   0.125    -.0195232    .1604267
          in1hostlev |  -.0633476   .1543814    -0.41   0.682    -.3659296    .2392344
               _cons |  -.2372511   .7172859    -0.33   0.741    -1.643106    1.168603
--------------------------------------------------------------------------------------
(est3 stored)

. restore

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A19: Dropping Some MIDs (Recip Model)") mtitles("Drop MIDs Beginning with Force" "Drop N
> on-Revisionist MIDs" "Retain Only One Observation per MID Target")
(output written to appendix.rtf)

. eststo clear

. 
. 
. * Table A20: Interaction
. eststo: probit recip reallycrazy15a##reallycrazy15b modcrazy15a##modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clu
> ster(ccodea)

note: 1.reallycrazy15a#1.reallycrazy15b identifies no observations in the sample
Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -498.86805  
Iteration 2:   log pseudolikelihood = -498.78612  
Iteration 3:   log pseudolikelihood = -498.78611  

Probit regression                               Number of obs     =        759
                                                Wald chi2(16)     =      90.95
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.78611               Pseudo R2         =     0.0386

                                                (Std. Err. adjusted for 114 clusters in ccodea)
-----------------------------------------------------------------------------------------------
                              |               Robust
                        recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------------+----------------------------------------------------------------
             1.reallycrazy15a |     .44242   .1533943     2.88   0.004     .1417728    .7430673
             1.reallycrazy15b |  -.5492837   .1996584    -2.75   0.006     -.940607   -.1579605
                              |
reallycrazy15a#reallycrazy15b |
                         1 1  |          0  (empty)
                              |
                1.modcrazy15a |  -.1559226   .2109387    -0.74   0.460    -.5693548    .2575096
                1.modcrazy15b |  -.2019468   .2252314    -0.90   0.370    -.6433922    .2394986
                              |
      modcrazy15a#modcrazy15b |
                         1 1  |  -.0296402   .4349326    -0.07   0.946    -.8820925     .822812
                              |
         recentMIDs_byleadera |   -.038661   .1063384    -0.36   0.716    -.2470803    .1697584
         recentMIDs_byleaderb |   .0985414   .0982962     1.00   0.316    -.0941156    .2911984
                        cinca |  -.2350536   2.175434    -0.11   0.914    -4.498826    4.028719
                        cincb |  -2.672209   1.578195    -1.69   0.090    -5.765415    .4209962
                     cincperc |   .2422308   .5205803     0.47   0.642    -.7780878    1.262549
                         dema |   -.196654   .2011231    -0.98   0.328    -.5908481    .1975401
                         demb |  -.0162894   .1568027    -0.10   0.917     -.323617    .2910382
                     jointdem |  -.1769474   .3012077    -0.59   0.557    -.7673035    .4134088
                   landcontig |   .3125472   .1357563     2.30   0.021     .0464697    .5786247
                     distance |   .0464984   .0423806     1.10   0.273    -.0365659    .1295628
                   in1hostlev |  -.0576961   .1473369    -0.39   0.695    -.3464711    .2310789
                        _cons |  -.1789493   .6012718    -0.30   0.766     -1.35742    .9995217
-----------------------------------------------------------------------------------------------
(est1 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A20: Interaction (Recip Model)")
(output written to appendix.rtf)

. margins, at(modcrazy15a=0 reallycrazy15a=0 modcrazy15b=0 reallycrazy15b=0 ) saving(file1, replace
> )

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           0
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .4522869   .0318951    14.18   0.000     .3897735    .5148002
------------------------------------------------------------------------------

. margins, at(modcrazy15a=0 reallycrazy15a=0 modcrazy15b=1 reallycrazy15b=0 ) saving(file2, replace
> ) 

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           0
               modcrazy15b     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .3755091   .0854459     4.39   0.000     .2080382      .54298
------------------------------------------------------------------------------

. margins, at(modcrazy15a=1 reallycrazy15a=0 modcrazy15b=0 reallycrazy15b=0 ) saving(file3, replace
> )

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           1
               modcrazy15b     =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .3926955   .0715125     5.49   0.000     .2525335    .5328575
------------------------------------------------------------------------------

. margins, at(modcrazy15a=1 reallycrazy15a=0 modcrazy15b=1 reallycrazy15b=0 ) saving(file4, replace
> )

Predictive margins                              Number of obs     =        759
Model VCE    : Robust

Expression   : Pr(recip), predict()
at           : reallycrazy15a  =           0
               reallycrazy15b  =           0
               modcrazy15a     =           1
               modcrazy15b     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .3089768   .1252582     2.47   0.014     .0634753    .5544783
------------------------------------------------------------------------------

. combomarginsplot file1 file2 file3 file4, recast(bar)

  Variables that uniquely identify margins: _filenumber

. graph save Graph "Slight_Rep_Interaction_Recip.gph", replace
(note: file Slight_Rep_Interaction_Recip.gph not found)
(file Slight_Rep_Interaction_Recip.gph saved)

. eststo clear 

. 
. * Table A21: Conflict Selection
. use "Dyadic Crazy Leader Data.dta", clear

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. merge m:1 dispnum3 ccodea ccodeb using "Crazy Leader MID Data.dta", keepusing(recip in1hostlev)

    Result                           # of obs.
    -----------------------------------------
    not matched                       815,112
        from master                   815,073  (_merge==1)
        from using                         39  (_merge==2)

    matched                             1,273  (_merge==3)
    -----------------------------------------

. drop if _merge==2 //These are cases in which more than one MID was initiated between the same cou
> ntries in the same year. Dispum3 in the directed-dyad-year data identifies the most serious dispu
> te, based on hostility and fatality.
(39 observations deleted)

. assert _merge==3 if initMID==1

. drop _merge

. 
. eststo: heckprobit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleade
> ra recentMIDs_byleaderb cincperc dema demb jointdem landcontig distance in1hostlev if pol_rel==1,
>  select(initMID=reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera recent
> MIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs pe
> aceyrs_sq peaceyrs_cub) cluster(ccodea)

Fitting probit model:

Iteration 0:   log pseudolikelihood = -360.21629  
Iteration 1:   log pseudolikelihood = -349.70817  
Iteration 2:   log pseudolikelihood = -349.69116  
Iteration 3:   log pseudolikelihood = -349.69116  

Fitting selection model:

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood =  -2459.833  
Iteration 2:   log pseudolikelihood = -2293.9348  
Iteration 3:   log pseudolikelihood = -2287.2539  
Iteration 4:   log pseudolikelihood = -2287.2008  
Iteration 5:   log pseudolikelihood = -2287.2008  

Fitting starting values:

Iteration 0:   log pseudolikelihood = -365.28856  
Iteration 1:   log pseudolikelihood = -349.55069  
Iteration 2:   log pseudolikelihood = -349.49888  
Iteration 3:   log pseudolikelihood = -349.49888  

Fitting full model:

Iteration 0:   log pseudolikelihood = -2636.6998  
Iteration 1:   log pseudolikelihood = -2636.6947  
Iteration 2:   log pseudolikelihood = -2636.6947  

Probit model with sample selection              Number of obs     =     62,384
                                                      Selected    =        527
                                                      Nonselected =     61,857

                                                Wald chi2(13)     =      70.29
Log pseudolikelihood = -2636.695                Prob > chi2       =     0.0000

                                       (Std. Err. adjusted for 169 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
                     |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
recip                |
      reallycrazy15a |   .8671256   .2562687     3.38   0.001     .3648481    1.369403
         modcrazy15a |  -.2365201   .2745534    -0.86   0.389    -.7746348    .3015946
      reallycrazy15b |  -.2494279   .2689635    -0.93   0.354    -.7765867    .2777309
         modcrazy15b |   -.294786   .1998929    -1.47   0.140    -.6865688    .0969968
recentMIDs_byleadera |  -.1433202   .1187547    -1.21   0.227     -.376075    .0894347
recentMIDs_byleaderb |   .0039729   .0843531     0.05   0.962    -.1613561    .1693018
            cincperc |   .0111152   .4197992     0.03   0.979    -.8116761    .8339065
                dema |  -.0919644   .2386076    -0.39   0.700    -.5596267    .3756979
                demb |   .0690873   .2257596     0.31   0.760    -.3733934    .5115681
            jointdem |  -.0852886    .447051    -0.19   0.849    -.9614925    .7909152
          landcontig |   .2458147   .1961378     1.25   0.210    -.1386084    .6302377
            distance |    .062145    .047508     1.31   0.191     -.030969    .1552589
          in1hostlev |   -.018019   .1095202    -0.16   0.869    -.2326747    .1966368
               _cons |   .0574696    .805736     0.07   0.943    -1.521744    1.636683
---------------------+----------------------------------------------------------------
initMID              |
      reallycrazy15a |   .1617635   .2118213     0.76   0.445    -.2533986    .5769257
         modcrazy15a |    .097694   .0815722     1.20   0.231    -.0621846    .2575726
      reallycrazy15b |   .9063581   .1584104     5.72   0.000     .5958794    1.216837
         modcrazy15b |   .1596137   .0685256     2.33   0.020      .025306    .2939213
recentMIDs_byleadera |   .2316819   .0644087     3.60   0.000     .1054432    .3579206
recentMIDs_byleaderb |    .048857   .0347938     1.40   0.160    -.0193376    .1170516
               cinca |   1.776548   .4944828     3.59   0.000     .8073799    2.745717
               cincb |   1.373534   .8309572     1.65   0.098    -.2551121     3.00218
            cincperc |  -.0180788   .2257845    -0.08   0.936    -.4606083    .4244507
                dema |     .10491   .0682302     1.54   0.124    -.0288188    .2386387
                demb |   .1013987   .0735048     1.38   0.168    -.0426682    .2454655
            jointdem |  -.4882736   .1373971    -3.55   0.000     -.757567   -.2189802
          landcontig |   .5385286   .0714225     7.54   0.000      .398543    .6785142
            distance |  -.1204417   .0323934    -3.72   0.000    -.1839317   -.0569518
          dyadlength |   .6279613   .0997835     6.29   0.000     .4323892    .8235335
            peaceyrs |  -.0424795   .0049885    -8.52   0.000    -.0522567   -.0327023
         peaceyrs_sq |   .0005359   .0000846     6.34   0.000     .0003702    .0007017
        peaceyrs_cub |  -1.84e-06   3.85e-07    -4.79   0.000    -2.60e-06   -1.09e-06
               _cons |  -2.631718   .1540264   -17.09   0.000    -2.933604   -2.329832
---------------------+----------------------------------------------------------------
             /athrho |  -.1079307   .2263231    -0.48   0.633    -.5515159    .3356545
---------------------+----------------------------------------------------------------
                 rho |  -.1075136    .223707                     -.5016555    .3235924
--------------------------------------------------------------------------------------
Wald test of indep. eqns. (rho = 0): chi2(1) =     0.23   Prob > chi2 = 0.6334
(est1 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) nocon compress labe
> l title("Table A21: Conflict Selection Model (Recip Model)")
(output written to appendix.rtf)

. eststo clear

. use "Crazy Leader MID Data", clear

. 
. * Note: Table A22 is the capabilities interaction above.
. 
. 
. 
. ************************************ FOOTNOTES **************************************************
> ****************
. 
. * Tables A23 and A24: Results cited in footnotes for deterrence model
. use "Dyadic Crazy Leader Data", clear

. //Retain tiny countries
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3130.8301  
Iteration 1:   log pseudolikelihood = -2528.4534  
Iteration 2:   log pseudolikelihood = -2350.8759  
Iteration 3:   log pseudolikelihood = -2343.6374  
Iteration 4:   log pseudolikelihood =  -2343.574  
Iteration 5:   log pseudolikelihood =  -2343.574  

Probit regression                               Number of obs     =     67,522
                                                Wald chi2(18)     =     895.55
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2343.574               Pseudo R2         =     0.2515

                                     (Std. Err. adjusted for 1,637 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1558883   .2104628     0.74   0.459    -.2566111    .5683877
         modcrazy15a |    .088694   .0704631     1.26   0.208    -.0494111    .2267991
      reallycrazy15b |   .9142253   .1401331     6.52   0.000     .6395694    1.188881
         modcrazy15b |   .1627597   .0744917     2.18   0.029     .0167586    .3087608
recentMIDs_byleadera |   .2410593   .0299188     8.06   0.000     .1824195     .299699
recentMIDs_byleaderb |   .0493011   .0314373     1.57   0.117     -.012315    .1109172
               cinca |   1.628554   .7662918     2.13   0.034     .1266494    3.130458
               cincb |    1.39596   .5752232     2.43   0.015     .2685428    2.523376
            cincperc |  -.0423838   .1623702    -0.26   0.794    -.3606235     .275856
                dema |   .0896015   .0589117     1.52   0.128    -.0258634    .2050663
                demb |   .1038187   .0596279     1.74   0.082    -.0130497    .2206872
            jointdem |  -.4811327    .105253    -4.57   0.000    -.6874247   -.2748406
          landcontig |   .5297396   .0695392     7.62   0.000     .3934453    .6660339
            distance |  -.1235781   .0235446    -5.25   0.000    -.1697246   -.0774316
          dyadlength |    .627939   .0768946     8.17   0.000     .4772284    .7786497
            peaceyrs |  -.0445399   .0040529   -10.99   0.000    -.0524834   -.0365965
         peaceyrs_sq |   .0005709   .0000761     7.51   0.000     .0004218      .00072
        peaceyrs_cub |  -1.98e-06   3.64e-07    -5.44   0.000    -2.69e-06   -1.27e-06
               _cons |  -2.608252   .1426265   -18.29   0.000    -2.887795   -2.328709
--------------------------------------------------------------------------------------
(est1 stored)

. drop if tpopa<500 | tpopb<500
(125,804 observations deleted)

. // Drop extreme outlier
. preserve

. drop if year==1997 & (ccodea==130 | ccodeb==130) // The high crazy score for Ecuador is actually 
> in 1996, but this is the year that needs dropping because of the lag.
(1,316 observations deleted)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peac
> eyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.4411  
Iteration 1:   log pseudolikelihood = -2459.6932  
Iteration 2:   log pseudolikelihood = -2293.6384  
Iteration 3:   log pseudolikelihood = -2286.9904  
Iteration 4:   log pseudolikelihood = -2286.9383  
Iteration 5:   log pseudolikelihood = -2286.9383  

Probit regression                               Number of obs     =     62,366
                                                Wald chi2(18)     =     861.46
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2286.9383               Pseudo R2         =     0.2478

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1643634   .2111887     0.78   0.436    -.2495588    .5782855
         modcrazy15a |   .0972413   .0706526     1.38   0.169    -.0412353    .2357178
      reallycrazy15b |   .9130613   .1409526     6.48   0.000     .6367992    1.189323
         modcrazy15b |   .1595945   .0746679     2.14   0.033     .0132481    .3059409
recentMIDs_byleadera |   .2315701   .0308121     7.52   0.000     .1711795    .2919606
recentMIDs_byleaderb |   .0481035   .0317843     1.51   0.130    -.0141926    .1103997
               cinca |   1.785435   .7726365     2.31   0.021     .2710949    3.299774
               cincb |   1.404192   .5836476     2.41   0.016     .2602635     2.54812
            cincperc |  -.0197502   .1706634    -0.12   0.908    -.3542443     .314744
                dema |   .1049455   .0607835     1.73   0.084    -.0141881     .224079
                demb |   .1021215   .0617198     1.65   0.098     -.018847    .2230901
            jointdem |  -.4888767   .1065082    -4.59   0.000    -.6976289   -.2801244
          landcontig |   .5389161   .0727776     7.40   0.000     .3962748    .6815575
            distance |  -.1207413   .0244487    -4.94   0.000    -.1686598   -.0728229
          dyadlength |   .6293184    .077637     8.11   0.000     .4771527    .7814842
            peaceyrs |  -.0424037   .0040398   -10.50   0.000    -.0503216   -.0344858
         peaceyrs_sq |   .0005345   .0000748     7.14   0.000     .0003878    .0006811
        peaceyrs_cub |  -1.84e-06   3.54e-07    -5.18   0.000    -2.53e-06   -1.14e-06
               _cons |  -2.633192   .1490036   -17.67   0.000    -2.925234    -2.34115
--------------------------------------------------------------------------------------
(est2 stored)

. restore

. // Alternate ways of counting recent previous MID initiations - broader and narrower.
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_statea re
> centMIDs_stateb cinca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs p
> eaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2478.2816  
Iteration 2:   log pseudolikelihood = -2308.1705  
Iteration 3:   log pseudolikelihood = -2301.3624  
Iteration 4:   log pseudolikelihood = -2301.3099  
Iteration 5:   log pseudolikelihood = -2301.3099  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     914.89
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2301.3099               Pseudo R2         =     0.2431

                                  (Std. Err. adjusted for 1,554 clusters in dyadid)
-----------------------------------------------------------------------------------
                  |               Robust
          initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
   reallycrazy15a |   .1178935   .2127058     0.55   0.579    -.2990022    .5347892
      modcrazy15a |   .1987007   .0703006     2.83   0.005     .0609141    .3364874
   reallycrazy15b |   .8686754   .1377167     6.31   0.000     .5987557    1.138595
      modcrazy15b |   .1610222   .0744835     2.16   0.031     .0150372    .3070071
recentMIDs_statea |   .0993036   .0150352     6.60   0.000     .0698351    .1287721
recentMIDs_stateb |   .0390807   .0158299     2.47   0.014     .0080547    .0701067
            cinca |   2.140124   .6977738     3.07   0.002     .7725126    3.507736
            cincb |   1.121602   .6248963     1.79   0.073    -.1031722    2.346376
         cincperc |  -.0804483   .1789705    -0.45   0.653    -.4312241    .2703275
             dema |   .0652078   .0627809     1.04   0.299    -.0578406    .1882561
             demb |   .1192657   .0598933     1.99   0.046      .001877    .2366543
         jointdem |  -.5034696   .1067992    -4.71   0.000    -.7127922   -.2941471
       landcontig |   .5453418   .0734032     7.43   0.000     .4014742    .6892094
         distance |  -.1223607   .0237385    -5.15   0.000    -.1688873   -.0758342
       dyadlength |   .6166366   .0775828     7.95   0.000     .4645771    .7686961
         peaceyrs |  -.0407404   .0040457   -10.07   0.000    -.0486699    -.032811
      peaceyrs_sq |   .0005093   .0000755     6.74   0.000     .0003612    .0006574
     peaceyrs_cub |  -1.73e-06   3.59e-07    -4.84   0.000    -2.44e-06   -1.03e-06
            _cons |  -2.610557   .1559064   -16.74   0.000    -2.916128   -2.304987
-----------------------------------------------------------------------------------
(est3 stored)

. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentlossMIDs_bylea
> dera recentlossMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance dyadlen
> gth peaceyrs peaceyrs_sq peaceyrs_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2495.3627  
Iteration 2:   log pseudolikelihood = -2334.5003  
Iteration 3:   log pseudolikelihood = -2328.5883  
Iteration 4:   log pseudolikelihood =  -2328.548  
Iteration 5:   log pseudolikelihood =  -2328.548  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(18)     =     814.79
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2328.548               Pseudo R2         =     0.2342

                                         (Std. Err. adjusted for 1,554 clusters in dyadid)
------------------------------------------------------------------------------------------
                         |               Robust
                 initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
          reallycrazy15a |   .2191332   .2101534     1.04   0.297    -.1927599    .6310263
             modcrazy15a |   .2530328   .0723064     3.50   0.000     .1113149    .3947507
          reallycrazy15b |   .8953952   .1385197     6.46   0.000     .6239016    1.166889
             modcrazy15b |   .1764968   .0766747     2.30   0.021      .026217    .3267765
recentlossMIDs_byleadera |   .4623527   .2725749     1.70   0.090    -.0718843    .9965897
recentlossMIDs_byleaderb |   .1653536   .3171819     0.52   0.602    -.4563115    .7870186
                   cinca |   3.224097   .5983896     5.39   0.000     2.051275    4.396919
                   cincb |   1.548521   .5698937     2.72   0.007     .4315499    2.665492
                cincperc |  -.1455387     .17978    -0.81   0.418    -.4979011    .2068236
                    dema |   .0600714   .0631209     0.95   0.341    -.0636433    .1837861
                    demb |   .1270721   .0605978     2.10   0.036     .0083025    .2458417
                jointdem |  -.5168112   .1071991    -4.82   0.000    -.7269177   -.3067048
              landcontig |   .5093244   .0717483     7.10   0.000     .3687004    .6499484
                distance |  -.1186301   .0236137    -5.02   0.000    -.1649121   -.0723482
              dyadlength |   .6238974   .0768917     8.11   0.000     .4731925    .7746023
                peaceyrs |  -.0456123   .0041786   -10.92   0.000    -.0538022   -.0374223
             peaceyrs_sq |   .0005785   .0000794     7.29   0.000      .000423    .0007341
            peaceyrs_cub |  -1.99e-06   3.85e-07    -5.17   0.000    -2.74e-06   -1.24e-06
                   _cons |  -2.417765   .1491675   -16.21   0.000    -2.710127   -2.125402
------------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A23: Tests Mentioned in Footnotes (Initiation Model)") mtitles("Retain Tiny Countries" "
> Drop Extreme Outlier" "Count Recent MIDs by Country" "Count Only Losing Recent MIDs by Leader")
(output written to appendix.rtf)

. eststo clear

. // Minimalist model
. eststo: probit initMID reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera
>  recentMIDs_byleaderb cincperc jointdem landcontig dyadlength peaceyrs peaceyrs_sq peaceyrs_cub i
> f pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2475.4355  
Iteration 2:   log pseudolikelihood = -2331.5921  
Iteration 3:   log pseudolikelihood = -2328.1552  
Iteration 4:   log pseudolikelihood = -2328.1519  
Iteration 5:   log pseudolikelihood = -2328.1519  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(13)     =     743.25
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2328.1519               Pseudo R2         =     0.2343

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .1507448   .2108679     0.71   0.475    -.2625486    .5640382
         modcrazy15a |   .0728765   .0702959     1.04   0.300     -.064901     .210654
      reallycrazy15b |   .8895675    .140274     6.34   0.000     .6146355    1.164499
         modcrazy15b |   .1388071   .0734392     1.89   0.059    -.0051311    .2827452
recentMIDs_byleadera |   .2390675   .0240942     9.92   0.000     .1918438    .2862912
recentMIDs_byleaderb |   .0519517    .028636     1.81   0.070    -.0041739    .1080773
            cincperc |  -.0120805   .1111252    -0.11   0.913    -.2298818    .2057209
            jointdem |   -.295028   .0822965    -3.58   0.000    -.4563261   -.1337298
          landcontig |   .7296352   .0592417    12.32   0.000     .6135236    .8457469
          dyadlength |   .5998874   .0765471     7.84   0.000     .4498579    .7499169
            peaceyrs |  -.0455598   .0042047   -10.84   0.000    -.0538008   -.0373189
         peaceyrs_sq |   .0005572   .0000825     6.76   0.000     .0003956    .0007188
        peaceyrs_cub |  -1.88e-06   4.04e-07    -4.65   0.000    -2.67e-06   -1.09e-06
               _cons |  -2.778745   .1122729   -24.75   0.000    -2.998796   -2.558694
--------------------------------------------------------------------------------------
(est1 stored)

. //Logged measure
. gen crazyscore_lna=ln(crazyscore_l1a+1)
(112,132 missing values generated)

. gen crazyscore_lnb=ln(crazyscore_l1b+1)
(112,132 missing values generated)

. eststo: probit initMID crazyscore_lna crazyscore_lnb recentMIDs_byleadera recentMIDs_byleaderb ci
> nca cincb cincperc dema demb jointdem landcontig distance dyadlength peaceyrs peaceyrs_sq peaceyr
> s_cub if pol_rel==1, cluster(dyadid)

Iteration 0:   log pseudolikelihood = -3040.5938  
Iteration 1:   log pseudolikelihood = -2458.6439  
Iteration 2:   log pseudolikelihood = -2293.7985  
Iteration 3:   log pseudolikelihood = -2286.9697  
Iteration 4:   log pseudolikelihood = -2286.9151  
Iteration 5:   log pseudolikelihood = -2286.9151  

Probit regression                               Number of obs     =     62,384
                                                Wald chi2(16)     =     873.43
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2286.9151               Pseudo R2         =     0.2479

                                     (Std. Err. adjusted for 1,554 clusters in dyadid)
--------------------------------------------------------------------------------------
                     |               Robust
             initMID |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_lna |   .3437952   .1860765     1.85   0.065    -.0209081    .7084985
      crazyscore_lnb |   .9231331   .1393129     6.63   0.000     .6500849    1.196181
recentMIDs_byleadera |   .2362378   .0309691     7.63   0.000     .1755396    .2969361
recentMIDs_byleaderb |     .05009   .0312703     1.60   0.109    -.0111987    .1113787
               cinca |   1.834219   .7626309     2.41   0.016     .3394903    3.328949
               cincb |   1.436974   .5723711     2.51   0.012     .3151473    2.558801
            cincperc |  -.0122873   .1640471    -0.07   0.940    -.3338138    .3092392
                dema |   .1210456   .0614477     1.97   0.049     .0006103     .241481
                demb |   .1042084   .0610757     1.71   0.088    -.0154977    .2239146
            jointdem |  -.4962643   .1065792    -4.66   0.000    -.7051557   -.2873729
          landcontig |   .5346357   .0714687     7.48   0.000     .3945596    .6747117
            distance |  -.1204988     .02473    -4.87   0.000    -.1689687    -.072029
          dyadlength |   .6589997   .0798985     8.25   0.000     .5024015    .8155978
            peaceyrs |  -.0416827   .0040386   -10.32   0.000    -.0495983   -.0337671
         peaceyrs_sq |   .0005224   .0000757     6.90   0.000      .000374    .0006708
        peaceyrs_cub |  -1.79e-06   3.60e-07    -4.96   0.000    -2.49e-06   -1.08e-06
               _cons |  -2.672642   .1464655   -18.25   0.000    -2.959709   -2.385575
--------------------------------------------------------------------------------------
(est2 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A24: More Tests Mentioned in Footnotes (Initiation Model)") mtitles("Minimalist Model" "
> Logged Madness Measure")
(output written to appendix.rtf)

. eststo clear

. 
. * Tables A25 and A26: Results cited in footnotes for crisis bargaining model
. //Retain tiny countries
. use "Crazy Leader MID Data", clear

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodea)

Iteration 0:   log pseudolikelihood = -527.80555  
Iteration 1:   log pseudolikelihood = -506.99006  
Iteration 2:   log pseudolikelihood = -506.90892  
Iteration 3:   log pseudolikelihood = -506.90891  

Probit regression                               Number of obs     =        773
                                                Wald chi2(15)     =      99.58
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -506.90891               Pseudo R2         =     0.0396

                                       (Std. Err. adjusted for 119 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4620231   .1430526     3.23   0.001     .1816451    .7424012
         modcrazy15a |  -.1419579   .2095134    -0.68   0.498    -.5525967    .2686809
      reallycrazy15b |  -.5247993   .1995205    -2.63   0.009    -.9158522   -.1337464
         modcrazy15b |   -.195283   .1754419    -1.11   0.266    -.5391428    .1485769
recentMIDs_byleadera |  -.0570323    .096205    -0.59   0.553    -.2455907    .1315261
recentMIDs_byleaderb |   .0902427   .0971891     0.93   0.353    -.1002446    .2807299
               cinca |  -.1379988   2.153874    -0.06   0.949    -4.359514    4.083516
               cincb |  -2.520592   1.582231    -1.59   0.111    -5.621707    .5805233
            cincperc |    .196062   .5251463     0.37   0.709    -.8332058     1.22533
                dema |  -.1771194   .1982074    -0.89   0.372    -.5655988      .21136
                demb |   .0418007   .1590792     0.26   0.793    -.2699887    .3535901
            jointdem |  -.2270991   .3047056    -0.75   0.456    -.8243111    .3701129
          landcontig |   .3637755   .1370776     2.65   0.008     .0951084    .6324426
            distance |   .0495948   .0448751     1.11   0.269    -.0383589    .1375484
          in1hostlev |  -.0606876   .1497756    -0.41   0.685    -.3542424    .2328672
               _cons |  -.1986006   .6051957    -0.33   0.743    -1.384762    .9875612
--------------------------------------------------------------------------------------
(est1 stored)

. drop if tpopa<500 | tpopb<500
(19 observations deleted)

. // Alternate ways of counting previous MIDs - broader and narrower.
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_statea rece
> ntMIDs_stateb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, cluster(cco
> dea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -488.90062  
Iteration 2:   log pseudolikelihood = -488.76701  
Iteration 3:   log pseudolikelihood = -488.76701  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =     157.39
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -488.76701               Pseudo R2         =     0.0579

                                    (Std. Err. adjusted for 114 clusters in ccodea)
-----------------------------------------------------------------------------------
                  |               Robust
            recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
   reallycrazy15a |   .2448268   .1168757     2.09   0.036     .0157547     .473899
      modcrazy15a |  -.2226752   .2020833    -1.10   0.271    -.6187513    .1734008
   reallycrazy15b |    -.71052   .1985756    -3.58   0.000    -1.099721   -.3213191
      modcrazy15b |  -.2599914   .1766751    -1.47   0.141    -.6062683    .0862855
recentMIDs_statea |   .0907926   .0679763     1.34   0.182    -.0424384    .2240236
recentMIDs_stateb |    .172014   .0696376     2.47   0.014     .0355269    .3085011
            cinca |  -1.312292   1.830715    -0.72   0.473    -4.900426    2.275843
            cincb |  -4.293328    1.73986    -2.47   0.014     -7.70339    -.883265
         cincperc |   .1614321     .46413     0.35   0.728     -.748246     1.07111
             dema |  -.1637595   .2257147    -0.73   0.468    -.6061521    .2786331
             demb |  -.0253876   .1634745    -0.16   0.877    -.3457918    .2950166
         jointdem |  -.1491025    .302411    -0.49   0.622    -.7418173    .4436122
       landcontig |   .3426403   .1414363     2.42   0.015     .0654302    .6198504
         distance |   .0198539   .0416308     0.48   0.633    -.0617409    .1014487
       in1hostlev |  -.0151059   .1272078    -0.12   0.905    -.2644285    .2342168
            _cons |  -.5262163   .5356987    -0.98   0.326    -1.576166    .5237338
-----------------------------------------------------------------------------------
(est2 stored)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentlossMIDs_byleade
> ra recentlossMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostle
> v, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -498.78451  
Iteration 2:   log pseudolikelihood =  -498.6925  
Iteration 3:   log pseudolikelihood = -498.69248  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      77.53
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.69248               Pseudo R2         =     0.0388

                                           (Std. Err. adjusted for 114 clusters in ccodea)
------------------------------------------------------------------------------------------
                         |               Robust
                   recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
          reallycrazy15a |   .4310763   .1634245     2.64   0.008     .1107701    .7513825
             modcrazy15a |  -.1991476   .2018652    -0.99   0.324    -.5947961    .1965009
          reallycrazy15b |  -.5352923   .1959459    -2.73   0.006    -.9193393   -.1512453
             modcrazy15b |  -.1905904   .1828113    -1.04   0.297    -.5488941    .1677132
recentlossMIDs_byleadera |  -.1547995   .6597232    -0.23   0.814    -1.447833    1.138234
recentlossMIDs_byleaderb |   1.015748   .8739616     1.16   0.245    -.6971857    2.728681
                   cinca |   -.478203   1.856857    -0.26   0.797    -4.117577    3.161171
                   cincb |  -2.065323    1.67124    -1.24   0.217    -5.340893    1.210247
                cincperc |   .2820957   .5129481     0.55   0.582    -.7232642    1.287456
                    dema |  -.1992742   .2039323    -0.98   0.328    -.5989742    .2004258
                    demb |  -.0025545    .166677    -0.02   0.988    -.3292355    .3241265
                jointdem |  -.1663006   .3063082    -0.54   0.587    -.7666536    .4340525
              landcontig |   .3205324   .1429033     2.24   0.025      .040447    .6006178
                distance |   .0480568   .0438873     1.10   0.274    -.0379608    .1340744
              in1hostlev |   -.047147   .1461735    -0.32   0.747    -.3336418    .2393478
                   _cons |  -.2466944   .6033568    -0.41   0.683    -1.429252    .9358633
------------------------------------------------------------------------------------------
(est3 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A25: More Tests Mentioned in Footnotes (Recip Model)") mtitles("Retain Tiny Countries" "
> Count All Recent MIDs" "Count Only Recent Losing MIDs Initiated by Leader")
(output written to appendix.rtf)

. eststo clear

. // Minimalist model
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cincperc dema demb landcontig in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -500.89133  
Iteration 2:   log pseudolikelihood = -500.82482  
Iteration 3:   log pseudolikelihood = -500.82481  

Probit regression                               Number of obs     =        759
                                                Wald chi2(11)     =      52.58
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -500.82481               Pseudo R2         =     0.0347

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4198045   .1514135     2.77   0.006     .1230396    .7165695
         modcrazy15a |  -.1245689   .2138806    -0.58   0.560     -.543767    .2946293
      reallycrazy15b |  -.5149861   .1962154    -2.62   0.009    -.8995611   -.1304111
         modcrazy15b |  -.1887353   .1842496    -1.02   0.306     -.549858    .1723873
recentMIDs_byleadera |  -.0262395    .102292    -0.26   0.798    -.2267282    .1742491
recentMIDs_byleaderb |   .0663905   .0982149     0.68   0.499    -.1261073    .2588882
            cincperc |   .0397584   .4472452     0.09   0.929    -.8368261    .9163429
                dema |  -.2389374   .1454651    -1.64   0.100    -.5240439     .046169
                demb |  -.0780726    .126616    -0.62   0.537    -.3262354    .1700902
          landcontig |   .2573288   .1401467     1.84   0.066    -.0173537    .5320114
          in1hostlev |  -.0631234   .1486233    -0.42   0.671    -.3544196    .2281728
               _cons |   .0077565   .5830173     0.01   0.989    -1.134936    1.150449
--------------------------------------------------------------------------------------
(est1 stored)

. //Logged measure
. gen crazyscore_lna=ln(crazyscore_l1a+1)
(97 missing values generated)

. gen crazyscore_lnb=ln(crazyscore_l1b+1)
(63 missing values generated)

. eststo: probit recip crazyscore_lna crazyscore_lnb recentMIDs_byleadera recentMIDs_byleaderb cinc
> a cincb cincperc dema demb jointdem landcontig distance in1hostlev, cluster(ccodea)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood = -502.20825  
Iteration 2:   log pseudolikelihood = -502.17617  
Iteration 3:   log pseudolikelihood = -502.17617  

Probit regression                               Number of obs     =        759
                                                Wald chi2(13)     =      66.71
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -502.17617               Pseudo R2         =     0.0321

                                       (Std. Err. adjusted for 114 clusters in ccodea)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      crazyscore_lna |   .4296466   .1631627     2.63   0.008     .1098536    .7494396
      crazyscore_lnb |  -.1606845   .2403951    -0.67   0.504    -.6318502    .3104812
recentMIDs_byleadera |  -.0450569   .1031751    -0.44   0.662    -.2472764    .1571625
recentMIDs_byleaderb |   .0759651   .0945847     0.80   0.422    -.1094175    .2613478
               cinca |  -.1995833   2.103421    -0.09   0.924    -4.322213    3.923046
               cincb |    -2.5094   1.556971    -1.61   0.107    -5.561008    .5422073
            cincperc |   .3040468   .5457311     0.56   0.577    -.7655666     1.37366
                dema |  -.2402811   .2005529    -1.20   0.231    -.6333576    .1527953
                demb |   -.009594   .1614644    -0.06   0.953    -.3260584    .3068704
            jointdem |  -.1363125   .3045478    -0.45   0.654    -.7332152    .4605902
          landcontig |   .3637019   .1337133     2.72   0.007     .1016287    .6257751
            distance |   .0367117   .0400778     0.92   0.360    -.0418392    .1152627
          in1hostlev |  -.0487079   .1503807    -0.32   0.746    -.3434487    .2460328
               _cons |  -.2954646   .6058248    -0.49   0.626    -1.482859    .8919303
--------------------------------------------------------------------------------------
(est2 stored)

. // Cluster by different things
. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(leadida)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood =  -498.8694  
Iteration 2:   log pseudolikelihood = -498.78813  
Iteration 3:   log pseudolikelihood = -498.78812  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      45.69
                                                Prob > chi2       =     0.0001
Log pseudolikelihood = -498.78812               Pseudo R2         =     0.0386

                                      (Std. Err. adjusted for 224 clusters in leadida)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4423026    .212851     2.08   0.038     .0251224    .8594829
         modcrazy15a |   -.159595   .2102796    -0.76   0.448    -.5717354    .2525454
      reallycrazy15b |  -.5487059   .2443698    -2.25   0.025    -1.027662   -.0697498
         modcrazy15b |  -.2073286   .1675536    -1.24   0.216    -.5357276    .1210703
recentMIDs_byleadera |  -.0383996   .0993189    -0.39   0.699    -.2330612    .1562619
recentMIDs_byleaderb |   .0984017   .0978079     1.01   0.314    -.0932983    .2901017
               cinca |  -.2385955   1.543959    -0.15   0.877    -3.264699    2.787508
               cincb |   -2.67149   1.763663    -1.51   0.130    -6.128207     .785227
            cincperc |   .2421607   .4650049     0.52   0.603    -.6692321    1.153553
                dema |  -.1968972   .1604082    -1.23   0.220    -.5112915    .1174971
                demb |  -.0160729   .1540761    -0.10   0.917    -.3180565    .2859106
            jointdem |  -.1767771   .2476188    -0.71   0.475     -.662101    .3085469
          landcontig |   .3124347   .1312754     2.38   0.017     .0551396    .5697298
            distance |   .0465961   .0401444     1.16   0.246    -.0320855    .1252777
          in1hostlev |  -.0574566   .1449099    -0.40   0.692    -.3414748    .2265616
               _cons |  -.1794699   .5345375    -0.34   0.737    -1.227144    .8682044
--------------------------------------------------------------------------------------
(est3 stored)

. eststo: probit recip reallycrazy15a modcrazy15a reallycrazy15b modcrazy15b recentMIDs_byleadera r
> ecentMIDs_byleaderb cinca cincb cincperc dema demb jointdem landcontig distance in1hostlev, clust
> er(ccodeb)

Iteration 0:   log pseudolikelihood = -518.81252  
Iteration 1:   log pseudolikelihood =  -498.8694  
Iteration 2:   log pseudolikelihood = -498.78813  
Iteration 3:   log pseudolikelihood = -498.78812  

Probit regression                               Number of obs     =        759
                                                Wald chi2(15)     =      51.88
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -498.78812               Pseudo R2         =     0.0386

                                       (Std. Err. adjusted for 129 clusters in ccodeb)
--------------------------------------------------------------------------------------
                     |               Robust
               recip |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
      reallycrazy15a |   .4423026   .3618072     1.22   0.222    -.2668264    1.151432
         modcrazy15a |   -.159595   .1850442    -0.86   0.388    -.5222749    .2030849
      reallycrazy15b |  -.5487059   .3833268    -1.43   0.152    -1.300013    .2026008
         modcrazy15b |  -.2073286   .2120485    -0.98   0.328     -.622936    .2082787
recentMIDs_byleadera |  -.0383996   .0729193    -0.53   0.598    -.1813189    .1045196
recentMIDs_byleaderb |   .0984017   .1325677     0.74   0.458    -.1614263    .3582296
               cinca |  -.2385955   1.584251    -0.15   0.880     -3.34367    2.866479
               cincb |   -2.67149   1.954646    -1.37   0.172    -6.502527    1.159547
            cincperc |   .2421607   .3987997     0.61   0.544    -.5394724    1.023794
                dema |  -.1968972   .1530233    -1.29   0.198    -.4968173    .1030229
                demb |  -.0160729   .1460621    -0.11   0.912    -.3023494    .2702035
            jointdem |  -.1767771    .243239    -0.73   0.467    -.6535168    .2999627
          landcontig |   .3124347   .1384674     2.26   0.024     .0410436    .5838258
            distance |   .0465961   .0402825     1.16   0.247     -.032356    .1255483
          in1hostlev |  -.0574566   .1003557    -0.57   0.567    -.2541502     .139237
               _cons |  -.1794699   .4176385    -0.43   0.667    -.9980262    .6390865
--------------------------------------------------------------------------------------
(est4 stored)

. esttab using appendix.rtf, append b(3) se(3) lines star(* .10 ** .05 *** .01) compress label titl
> e("Table A26: Tests Mentioned in Footnotes (Recip Model)") mtitles("Minimalist Model" "Logged Mad
> ness Measure" "Cluster by Leader A" "Cluster by Country B")
(output written to appendix.rtf)

. eststo clear

. 
. 
end of do-file

. exit, clear
